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DTSTAMP:20251125T101901
DTSTART;TZID=America/Detroit:20251125T180000
DTEND;TZID=America/Detroit:20251125T190000
SUMMARY:Livestream / Virtual:2025 MPSDS Master's Program Information Session
DESCRIPTION:November 25\, 2025\n6:00PM - 7:00PM (EST)\nRegistration Required\n\nThe Michigan Program of Survey and Data Science (MPSDS) trains future generations of survey and data scientists at the intersection of social research and data science. Join us for our virtual information session to learn more about our master's program and the admissions process. \n\nThe Michigan Program in Survey and Data Science curriculum is concerned with a broad set of data sources\, including survey data\, social media posts\, sensor data\, and administrative records\, as well as analytic methods for working with these new data sources. We bring a strong focus on data quality — something often missing in traditional data science programs.\n\nFind out additional information about the program and our admissions process on our website or contact the program at MPSDS.isr@umich.edu. \n\nThis session will be recorded and posted on the department's website following the conclusion of the event.
UID:142189-21890190@events.umich.edu
URL:https://events.umich.edu/event/142189
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20251125T103050
DTSTART;TZID=America/Detroit:20251202T180000
DTEND;TZID=America/Detroit:20251202T190000
SUMMARY:Livestream / Virtual:2025 MPSDS PhD Program Information Session
DESCRIPTION:December 2\, 2025\n6:00PM-7:00PM\nRegistration Required\n\nThe Michigan Program of Survey and Data Science (MPSDS) trains future generations of survey and data scientists at the intersection of social research and data science. Join us for our virtual information session to learn more about our master's program and the admissions process.\n\nThe Michigan Program in Survey and Data Science curriculum is concerned with a broad set of data sources\, including survey data\, social media posts\, sensor data\, and administrative records\, as well as analytic methods for working with these new data sources. We bring a strong focus on data quality — something often missing in traditional data science programs.\n\nFind out additional information about the program and our admissions process on our website or contact the program at MPSDS.isr@umich.edu.\n\nThis session will be recorded and posted on the department's website following the conclusion of the event.
UID:142192-21890194@events.umich.edu
URL:https://events.umich.edu/event/142192
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20250611T152053
DTSTART;TZID=America/Detroit:20251208T100000
DTEND;TZID=America/Detroit:20251208T150000
SUMMARY:Class / Instruction:Summer Institute Course - December 2025- Health and Retirement Study (HRS) Workshop
DESCRIPTION:December 2025- Health and Retirement Study (HRS) Workshop\nDecember 8-10\, 2025\n10:00am-3:00pm EST\nLive Online via Zoom\n\nThe Health and Retirement Study (hrsonline.isr.umich.edu) Summer Workshop is intended to give participants an introduction to the study that will enable them to use the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow.\n\nDisability Data in the Health and Retirement Study (HRS) is a 3-day online (Zoom) workshop intended to give participants an overview of the disability data resources in the HRS. Content lectures delivered by HRS co-investigators and content area experts will cover a range of topics including:\n\n●        The various ways that disability\, disabling conditions\, health\, and functioning are measured in the HRS\;\n●        How measures of disability have changed as the survey has evolved\;\n●        How the HRS captures disability benefit receipt in the survey and through and linkage with data from the Social Security Administration\;\n●        How disability-related topics like employer accommodations\, assistive technology and personal assistance are measured in the survey.\n\nIn addition to presentations on these topics\, the workshop will feature labs focused on working with work disability measures in Section M and disability spell data in the RAND HRS.\n\nStudents will have the opportunity to present research ideas and receive feedback from the workshop faculty and other students.\n\nThe course is designed for those with experience using HRS data or for those who have taken the introductory HRS workshop. The data training portion assumes some familiarity with STATA.\n\nAmanda Sonnega is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she directs communication\, outreach\, and education efforts for the Health and Retirement Study. She received her Ph.D. through the Department of Health\, Behavior & Society at the Johns Hopkins University and completed a post-doctoral fellowship within the ISR program in Social Environment and Health. She has lectured in the UM School of Public Health\, teaching Psychosocial Factors in Health-related Behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.\n\nThe Summer Institute in Survey Research Techniques provides rigorous and high quality graduate level training in all phases of survey research. The noncredit courses are open to all. The courses are live online via Zoom. Registration and payment are required. Course fees are based on the total number of hours assigned to each course\, the hours are listed on the course description. The 2025 schedule lists additional courses. If you have any questions regarding the application process\, please use the online contact form or email the Summer Institute at isr-summer@umich.edu .\n\nThe program teaches state-of-the-art practice and theory in the design\, implementation\, and analysis of surveys. The Summer Institute in Survey Research Techniques has presented courses on the sample survey since the summer of 1948\, and has offered such courses every summer since. The Summer Institute uses the sample survey as the basic instrument for the scientific measurement of human activity. It presents sample survey methods in courses designed to meet the educational needs of those specializing in social and behavioral research such as professionals in business\, public health\, natural resources\, law\, medicine\, nursing\, social work\, and many other domains of study.
UID:136088-21877833@events.umich.edu
URL:https://events.umich.edu/event/136088
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20250611T152053
DTSTART;TZID=America/Detroit:20251209T100000
DTEND;TZID=America/Detroit:20251209T150000
SUMMARY:Class / Instruction:Summer Institute Course - December 2025- Health and Retirement Study (HRS) Workshop
DESCRIPTION:December 2025- Health and Retirement Study (HRS) Workshop\nDecember 8-10\, 2025\n10:00am-3:00pm EST\nLive Online via Zoom\n\nThe Health and Retirement Study (hrsonline.isr.umich.edu) Summer Workshop is intended to give participants an introduction to the study that will enable them to use the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow.\n\nDisability Data in the Health and Retirement Study (HRS) is a 3-day online (Zoom) workshop intended to give participants an overview of the disability data resources in the HRS. Content lectures delivered by HRS co-investigators and content area experts will cover a range of topics including:\n\n●        The various ways that disability\, disabling conditions\, health\, and functioning are measured in the HRS\;\n●        How measures of disability have changed as the survey has evolved\;\n●        How the HRS captures disability benefit receipt in the survey and through and linkage with data from the Social Security Administration\;\n●        How disability-related topics like employer accommodations\, assistive technology and personal assistance are measured in the survey.\n\nIn addition to presentations on these topics\, the workshop will feature labs focused on working with work disability measures in Section M and disability spell data in the RAND HRS.\n\nStudents will have the opportunity to present research ideas and receive feedback from the workshop faculty and other students.\n\nThe course is designed for those with experience using HRS data or for those who have taken the introductory HRS workshop. The data training portion assumes some familiarity with STATA.\n\nAmanda Sonnega is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she directs communication\, outreach\, and education efforts for the Health and Retirement Study. She received her Ph.D. through the Department of Health\, Behavior & Society at the Johns Hopkins University and completed a post-doctoral fellowship within the ISR program in Social Environment and Health. She has lectured in the UM School of Public Health\, teaching Psychosocial Factors in Health-related Behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.\n\nThe Summer Institute in Survey Research Techniques provides rigorous and high quality graduate level training in all phases of survey research. The noncredit courses are open to all. The courses are live online via Zoom. Registration and payment are required. Course fees are based on the total number of hours assigned to each course\, the hours are listed on the course description. The 2025 schedule lists additional courses. If you have any questions regarding the application process\, please use the online contact form or email the Summer Institute at isr-summer@umich.edu .\n\nThe program teaches state-of-the-art practice and theory in the design\, implementation\, and analysis of surveys. The Summer Institute in Survey Research Techniques has presented courses on the sample survey since the summer of 1948\, and has offered such courses every summer since. The Summer Institute uses the sample survey as the basic instrument for the scientific measurement of human activity. It presents sample survey methods in courses designed to meet the educational needs of those specializing in social and behavioral research such as professionals in business\, public health\, natural resources\, law\, medicine\, nursing\, social work\, and many other domains of study.
UID:136088-21877834@events.umich.edu
URL:https://events.umich.edu/event/136088
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20251121T102009
DTSTART;TZID=America/Detroit:20251209T103000
DTEND;TZID=America/Detroit:20251209T120000
SUMMARY:Lecture / Discussion:Theorizing Success in an Unfair Job Market
DESCRIPTION:Join the Stone Center for Inequality Dynamics as we host Maggie Frye\, Associate Professor of Sociology at U-M. Frye uses both qualitative and quantitative methods to investigate how shared cultural ideals and expectations shape outcomes during young adulthood\, with a particular focus on family formation and schooling. Most of Frye’s research has focused on sub-Saharan Africa\, with several projects in Malawi and Uganda as well as a number of studies that use data from dozens of African countries to learn about how unequally distributed educational opportunities shape cultural norms and behaviors. Frye recently completed a longitudinal data collection project in Kampala\, Uganda\, examining changing understandings of status resulting from Uganda’s simultaneous expansion of university education and contraction of formal employment opportunities.
UID:142103-21890009@events.umich.edu
URL:https://events.umich.edu/event/142103
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Institute For Social Research - 1430 BD
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20250611T152053
DTSTART;TZID=America/Detroit:20251210T100000
DTEND;TZID=America/Detroit:20251210T150000
SUMMARY:Class / Instruction:Summer Institute Course - December 2025- Health and Retirement Study (HRS) Workshop
DESCRIPTION:December 2025- Health and Retirement Study (HRS) Workshop\nDecember 8-10\, 2025\n10:00am-3:00pm EST\nLive Online via Zoom\n\nThe Health and Retirement Study (hrsonline.isr.umich.edu) Summer Workshop is intended to give participants an introduction to the study that will enable them to use the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow.\n\nDisability Data in the Health and Retirement Study (HRS) is a 3-day online (Zoom) workshop intended to give participants an overview of the disability data resources in the HRS. Content lectures delivered by HRS co-investigators and content area experts will cover a range of topics including:\n\n●        The various ways that disability\, disabling conditions\, health\, and functioning are measured in the HRS\;\n●        How measures of disability have changed as the survey has evolved\;\n●        How the HRS captures disability benefit receipt in the survey and through and linkage with data from the Social Security Administration\;\n●        How disability-related topics like employer accommodations\, assistive technology and personal assistance are measured in the survey.\n\nIn addition to presentations on these topics\, the workshop will feature labs focused on working with work disability measures in Section M and disability spell data in the RAND HRS.\n\nStudents will have the opportunity to present research ideas and receive feedback from the workshop faculty and other students.\n\nThe course is designed for those with experience using HRS data or for those who have taken the introductory HRS workshop. The data training portion assumes some familiarity with STATA.\n\nAmanda Sonnega is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she directs communication\, outreach\, and education efforts for the Health and Retirement Study. She received her Ph.D. through the Department of Health\, Behavior & Society at the Johns Hopkins University and completed a post-doctoral fellowship within the ISR program in Social Environment and Health. She has lectured in the UM School of Public Health\, teaching Psychosocial Factors in Health-related Behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.\n\nThe Summer Institute in Survey Research Techniques provides rigorous and high quality graduate level training in all phases of survey research. The noncredit courses are open to all. The courses are live online via Zoom. Registration and payment are required. Course fees are based on the total number of hours assigned to each course\, the hours are listed on the course description. The 2025 schedule lists additional courses. If you have any questions regarding the application process\, please use the online contact form or email the Summer Institute at isr-summer@umich.edu .\n\nThe program teaches state-of-the-art practice and theory in the design\, implementation\, and analysis of surveys. The Summer Institute in Survey Research Techniques has presented courses on the sample survey since the summer of 1948\, and has offered such courses every summer since. The Summer Institute uses the sample survey as the basic instrument for the scientific measurement of human activity. It presents sample survey methods in courses designed to meet the educational needs of those specializing in social and behavioral research such as professionals in business\, public health\, natural resources\, law\, medicine\, nursing\, social work\, and many other domains of study.
UID:136088-21877835@events.umich.edu
URL:https://events.umich.edu/event/136088
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20251125T103618
DTSTART;TZID=America/Detroit:20251217T080000
DTEND;TZID=America/Detroit:20251217T210000
SUMMARY:Livestream / Virtual:2025 MPSDS Master's Program Information Session
DESCRIPTION:December 17\, 2025\n8:00AM - 9:00AM (EST)\nRegistration Required\n\nThe Michigan Program of Survey and Data Science (MPSDS) trains future generations of survey and data scientists at the intersection of social research and data science. Join us for our virtual information session to learn more about our master's program and the admissions process.\n\nThe Michigan Program in Survey and Data Science curriculum is concerned with a broad set of data sources\, including survey data\, social media posts\, sensor data\, and administrative records\, as well as analytic methods for working with these new data sources. We bring a strong focus on data quality — something often missing in traditional data science programs.\n\nFind out additional information about the program and our admissions process on our website or contact the program at MPSDS.isr@umich.edu.\n\nThis session will be recorded and posted on the department's website following the conclusion of the event.
UID:142190-21890191@events.umich.edu
URL:https://events.umich.edu/event/142190
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260105T150249
DTSTART;TZID=America/Detroit:20260114T120000
DTEND;TZID=America/Detroit:20260114T133000
SUMMARY:Lecture / Discussion:“The Tax Treatment of Housing as a Source of Racial Inequality”
DESCRIPTION:Join the Stone Center for Inequality Dynamics as we host our own faculty member Joe LaBriola as he presents\, “The Tax Treatment of Housing as a Source of Racial Inequality.”\n\nAbstract: “In this talk\, I argue that the state contributes to cumulative advantage processes in United States housing markets through the tax treatment of homeownership\, which fuels house price growth and provides greater economic benefits to groups with high homeownership rates. I focus in particular on the effect of the mortgage interest deduction\, a federal tax expenditure that transfers tens of billions of dollars to homeowners each year\, on economic inequality between White and Black households. I document wide White-Black inequality in mortgage interest deduction benefits\, caused in large part by White-Black gaps in homeownership\, and demonstrate how the mortgage interest deduction has contributed to growth of the White-Black wealth gap in recent decades. However\, I also show that White-Black gaps in mortgage interest deduction benefits have narrowed over time\, due to falling mortgage interest rates and increases in the size of the standard deduction. These findings highlight how the effects of racialized tax policies depend on how institutional and macroeconomic conditions interact with racial gaps in factors that affect tax liabilities.”\n\nJoe LaBriola is a Research Assistant Professor at the University of Michigan’s Survey Research Center\, where he is Faculty at the Stone Center for Inequality Dynamics. His research examines the roots of social stratification in the contemporary United States\, with his current research focusing on the role of housing and housing policy in exacerbating racial and socioeconomic inequalities. Methodologically\, he uses econometric methods and microsimulation modeling to analyze survey and administrative data. His work has been published in leading sociology journals including the American Sociological Review\, Social Forces\, and Social Problems.\n\nLunch will be provided to all in-person attendees. Please RSVP to save your seat.
UID:143220-21892508@events.umich.edu
URL:https://events.umich.edu/event/143220
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Institute For Social Research - 6050
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260115T113240
DTSTART;TZID=America/Detroit:20260119T140000
DTEND;TZID=America/Detroit:20260119T163000
SUMMARY:Lecture / Discussion:Extending the Legacy: Innovations of the 25-Year Follow-up of the National Survey of American Life
DESCRIPTION:In 2001\, Dr. James Jackson launched the National Survey of American Life (NSAL)\, the first nationally-representative health survey of Black Americans ever conducted. The goals of the NSAL were to examine how factors like stress\, coping\, early-life experiences\, and cultural beliefs relate to mental health and psychiatric disorders within the Black population. Twenty-five years later\, the NSAL remains unparalleled in terms of its characterization of heterogeneity in psychological\, social\, behavioral and environmental factors within the Black population. In 2026\, we are now planning to reinterview this singular cohort to understand pathways of risk and resilience between psychosocial factors and dementia. To be successful\, this 25-year followup will need to be pioneering in the spirit of the original NSAL effort. This presentation will summarize the survey methodological innovations of the original NSAL and describe the new approaches we are applying in this follow-up effort. Collectively\, this program will demonstrate how foundational principles of interdisciplinary collaboration\, team science\, relationships\, and resiliency are essential in today’s efforts to conduct social science in the public interest.\n\nThis is a hybrid event at the Institute for Social Research with a live stream option available at https://myumi.ch/Nr4mW
UID:143024-21891957@events.umich.edu
URL:https://events.umich.edu/event/143024
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Institute For Social Research - 1430
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260107T161642
DTSTART;TZID=America/Detroit:20260128T120000
DTEND;TZID=America/Detroit:20260128T130000
SUMMARY:Lecture / Discussion:MPSDS / JPSM Seminar Series:  Sensitivity Analyses for Nonignorable Selection Bias When Estimating Subgroup Parameters in Nonprobability Samples: A Weighting Approach
DESCRIPTION:MPSDS / JPSM Seminar Series\nMPSDS M3 Series: Mastery\, Methodology\, Meetups\n\nIn person\, room 1070 Institute for Social Research\, and via Zoom. \nThe Zoom call will be locked 10 minutes after the start of the presentation.\n\nSensitivity Analyses for Nonignorable Selection Bias When Estimating Subgroup Parameters in Nonprobability Samples: A Weighting Approach\n\nSelection bias in survey estimates is a major concern\, affecting both nonprobability samples and probability samples with low response rates. The proxy-pattern mixture model (PPMM) offers a method for conducting a sensitivity that assumes a nonignorable selection mechanism\, where selection depends on survey outcomes of interest. This approach requires summary-level auxiliary information for the target population of interest from a reference data source. While PPMM methods have been successfully applied to derive overall population-level estimates\, extension to domain-level estimates is challenging when population-level summaries for the specific subgroup are unavailable. This occurs when the domain indicator is observed only in the survey\, or for complex intersectional subgroups where stable/reliable population-level auxiliary variable estimates are unavailable. To combat this issue\, we propose a novel approach: creating nonignorable selection weights based on the PPMM based on a re-expression of the PPMM as a selection model. These weights can be directly applied to calculate domain-level estimates\, circumventing the need for domain-specific population-level summaries of auxiliary variables. They rely on a single sensitivity parameter (ranging from 0 to 1) that captures a spectrum of nonresponse assumptions\, ranging from an ignorable mechanism to an extreme nonignorable mechanism. We discuss differences in weight construction for continuous versus binary outcomes\, describe the necessary assumptions for these weights to produce informative domain-level estimates\, and illustrate properties through simulation. We then apply the approach to the Census Household Pulse Survey to estimate various subgroup quantities under a range of assumptions on the selection mechanism.\n\nRebecca R. Andridge\, PhD\nThe Ohio State University\nCollege of Public Health\, Division of Biostatistics\nAssociate Dean for Undergraduate Studies\nProfessor of Biostatistics\n\nDr. Andridge's research is focused on imputation methods for missing data\, primarily when missingness is driven by the missing values themselves (missing not at random)\, and on measures of selection bias for nonprobability samples. She also works on statistical challenges that arise in analysis of data from group-randomized trials. She collaborates with researchers across campus\, including the Institute for Behavioral Medicine Research\, the Nisonger Center for Excellence in Developmental Disabilities\, and The OSU Comprehensive Cancer Center\, and serves as Lead Methodologist for several state-sponsored population-based surveys. She is an Elected Fellow of the American Statistical Association (2020).
UID:143425-21893147@events.umich.edu
URL:https://events.umich.edu/event/143425
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location - Room 1070, Institute for Social Research
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20250924T145336
DTSTART;TZID=America/Detroit:20260218T120000
DTEND;TZID=America/Detroit:20260218T130000
SUMMARY:Lecture / Discussion:MPSDS JPSM Seminar Series - Rethinking Methods in the Global Attitudes Project: Explorations in Australia and Sweden
DESCRIPTION:MPSDS JPSM Seminar Series\nMPSDS M3 Series\n\nFebruary 18\, 2026\n12:00 - 1:00 pm EST\nIn person\, room 1070 Institute for Social Research\, and via Zoom. The Zoom call will be locked 10 minutes are the start of the presentation.\n\nRethinking Methods in the Global Attitudes Project: Explorations in Australia and Sweden\n\nIn addition to regularly surveying the American public\, Pew Research Center fields cross-national public opinion surveys in more than 20 countries annually as part of its Global Attitudes Project (GAP). The Center’s International Methods team focuses on designing\, implementing\, monitoring\, and improving these surveys throughout the year. In this talk\, we present two research projects from 2025 in Australia and Sweden.\n\nMany surveys around the world\, across modes and methods\, have tended to show a slight left-leaning political bias. Weighting to past vote or party affiliation is a common solution\, but these corrections alone may create excessive variance inflation. We faced this problem in our surveys fielded on the mixed-mode Life in Australia probability panel\, administered by the Australian National University’s Social Research Centre. To combat this bias\, we tested a “voting-adjusted” sampling approach recommended by our partners at SRC\, in parallel with our previous standard stratified sampling design. Taking advantage of panel information and recent Australian elections\, the new method incorporates self-reported 2022 vote into individual weights which are used as a measure of size for PPS sampling. After reviewing the technical details behind this approach\, we’ll discuss our findings on its impact on variance and substantive estimates compared to the standard design.\n\nPush-to-web (P2W) designs are gaining traction in Europe as an alternative to costly – and methodologically challenged – interviewer-administered approaches. For instance\, the European Social Survey announced that by 2027 online and paper self-administered surveys will be their primary means of data collection replacing their traditional face-to-face approach. To better understand this mode and its potential for future waves of GAP\, we recently piloted an ABS-style\, sequential P2W survey in Sweden to compare with our traditional dual-frame phone design (DFRDD). Our presentation will compare P2W and DFRDD sample outcomes in terms of data quality (such as response rates\, response differentiation\, survey engagement\, and open-ended answer quality)\, representativeness (versus demographic parameters for gender\, education\, age and geography) and attitudinal estimates (considering the viability of long-term data trends if mode transitioned in Sweden). The P2W survey included an unconditional incentive experiment as well as a paper questionnaire mailing\, allowing us to present findings regarding the value of these design elements. This section of the talk concludes with key takeaways and recommendations for future mode-transition trials. \n\nSofi Sinozich is a research methodologist in international methods at Pew Research Center. She advises on complex sample design\, survey implementation\, and data quality assessment for international projects across the Center. Prior to joining the Center\, she was a senior research analyst at Langer Research Associates\, where she managed and contributed to a wide variety of survey projects\, including serving as lead analyst on the ABC News/Washington Post poll. She holds a master's degree in survey methodology from JPSM and is a member of the WAPOR Professional Standards committee.\n\nPatrick Moynihan is the associate director of international methods at Pew Research Center. Prior to joining the Center\, Patrick was the survey methodologist in the U.S. Department of State’s Office of Opinion Research (INR/OPN)\, assistant director of the Program on Survey Research at Harvard University\, and senior polling analyst at ABC News. He is a past president of the New England Chapter of the American Association for Public Opinion Research (AAPOR)\, served on multiple national AAPOR committees\, and is currently a member of the Committee on Professional Standards for the World Association for Public Opinion Research. Moynihan received his doctorate in sociology from SUNY Stony Brook.
UID:139829-21886103@events.umich.edu
URL:https://events.umich.edu/event/139829
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location - Room 1070, Institute for Social Research
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260316T122849
DTSTART;TZID=America/Detroit:20260325T120000
DTEND;TZID=America/Detroit:20260325T130000
SUMMARY:Workshop / Seminar:MPSDS / JPSM Seminar Series: From Survey to SurvAI:  The Promises and Precautions of AI for Survey Research
DESCRIPTION:MPSDS / JPSM Seminar Series\nMPSDS M3 Series: Mastery\, Methodology\, Meetups\n\nIn person\, room 1070 Institute for Social Research\, and via Zoom.\nThe Zoom call will be locked 10 minutes after the start of the presentation.\n\nFrom Survey to SurvAI:  The Promises and Precautions of AI for Survey Research\n\nLarge language models (LLMs) are rapidly transforming many professional domains\, including survey research. Eloundou et al. (2024) rank survey research among the most highly exposed occupations to LLM-driven automation\, raising both opportunities and challenges for practitioners. While survey science has a rich tradition of adopting technological tools for tasks like data collection\, analysis\, and instrument design\, the unique affordances and risks associated with LLMs call for a structured examination.\n\nThis paper presents findings from a systematic literature review of empirical and theoretical work at the intersection of LLMs and survey research.  Specifically\, we sought to synthesize examples of how LLMs are being applied across three broad phases of the survey research pipeline including: pre-data collection\, data collection and post-data collection.  Methodologically\, this review identifies uneven distribution of LLM application across the survey pipeline. While pre-data collection stages (e.g.\, item writing\, translation) are well explored\, core practices like live interviewing\, recruitment\, and cross-lingual adaptation remain under-investigated. Additionally\, few studies assess LLMs systematically across multiple populations\, languages\, or survey topics. In this presentation we will highlight not just the breadth of current use cases\, but also the methodological and ethical considerations that must accompany them noting examples that are both promising as well as precautionary.\n\nTrent D. Buskirk\, Ph.D.  has recently joined the new School of Data Science at Old Dominion University.  Prior to this appointment\, Trent was the Novak Family Distinguished Professor of Data Science and outgoing Chair of the Applied Statistics and Operations Research Department at Bowling Green State University.  Dr. Buskirk is a Fellow of the American Statistical Association and his research is positioned at the intersection of survey science\, data science\, computational social science\, and human–AI interaction.  His specific research interests include Schema-Driven LLM-Based Inference\, big data quality\, recruitment methods through social media\, the use of big data and machine learning methods for health\, social and survey science design and analysis\, mobile and smartphone survey designs and in methods for calibrating and weighting samples and fairness in AI models and interpretable ML methods.  Trent has also been involved in various professional organizations serving as the President of the Midwest Association for Public Opinion Research in 2016\, the Conference Chair for AAPOR in 2018 and a member of the scientific committee for the BigSurv series of conferences since 2018.  Trent as also served as an Associate Editor (Methods) for the Journal of Survey Statistics and Methodology.    Dr. Buskirk is currently serving on the AAPOR Responsible Integration of AI in Survey Research task force.  When Trent is not geeking out over data science or survey research\, he’s likely out playing a competitive game of Pickleball!
UID:146650-21899402@events.umich.edu
URL:https://events.umich.edu/event/146650
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location - Institute for Social Research, Room 1070, Ann Arbor MI
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260313T083958
DTSTART;TZID=America/Detroit:20260327T110000
DTEND;TZID=America/Detroit:20260327T150000
SUMMARY:Lecture / Discussion:AI for Better Social Science: Capabilities and Challenges with Survey Research
DESCRIPTION:Register to receive Zoom link at https://myumi.ch/n1dDV \n\nProgram: \n\nAI-Assisted Conversational Interviewing: Effects on Data Quality and Respondent Experience \nSoubhik Barari\, Senior Research Methodologist at NORC at the University of Chicago\, working on applied problems at the intersection of survey methodology\, data science\, and AI. \n\nAbstract: Standardized surveys scale efficiently but often lack depth\, while conversational interviews improve response quality but are costly and inconsistent. This study advances a framework for AI‑assisted conversational interviewing to bridge this divide and demonstrates evidence of its practical utility. In a web survey experiment with 1\,800 participants\, we deployed AI “chatbots” powered by large language models to probe respondents for elaboration and to code open‑ended answers in real time. The chatbots achieved reasonably strong accuracy in live coding\, though they exhibited some over-identification of themes\, partly reflecting respondents’ tendency to agree with AI suggestions. They elicited richer\, more detailed responses compared to standard surveys\, with only small trade‑offs in respondent experience. Overall\, our results demonstrate that AI‑supported conversational tools can meaningfully enhance the depth and quality of open‑ended data collection\, pointing to a new generation of scalable\, adaptive survey methods.\n\nLLMs as Synthetic Respondents: A Tool for Augmenting Human Surveys\nSerina Chang\, Assistant Professor at UC Berkeley\, jointly appointed in EECS and Computational Precision Health and part of the Berkeley AI Research (BAIR) Lab. \n\nAbstract: Surveys are an invaluable resource for understanding human opinions and behaviors\, but they require substantial time and effort. Large language models (LLMs) present new opportunities to predict responses to survey questions\, given their natural language abilities and social knowledge acquired during pretraining. Integrating LLMs as synthetic respondents into survey pipelines could improve efficiency across multiple stages—from pre-survey pilot testing and sampling design to post-survey data imputation and analysis—not as a replacement for human participants but as a way to augment existing workflows. However\, these opportunities also raise new challenges\, including how to accurately reflect the opinions of diverse subpopulations\, generalize to questions outside LLM training data\, and reduce computational costs. In this talk\, I describe how we address these challenges in our work. First\, we show that fine-tuning LLMs on survey data substantially improves their ability to predict public opinion\, generalizing to unseen surveys and subgroups. In complementary work\, rather than fine-tuning with additional data\, we leverage knowledge already encoded in the LLM\, showing with probes and sparse autoencoders that models contain far more internal knowledge of human opinions than their outputs reveal. Finally\, we present graph-based approaches as a lightweight alternative: a graph model equipped with language representations from LLMs—but requiring no further LLM training or inference—can match LLM performance on some survey tasks while using orders of magnitude less compute.\n\nValidation and Inference for Survey Research Using Silicon Sampling \nLisa Argyle\, Associate Professor of Political Science at Purdue\n\nAbstract: In both research and commercial applications\, AI is increasingly being used to create synthetic representations of humans. This raises at least two important questions for scientists as they consider the integration of this new tool: How can a researcher know if the silicon survey output is valid? And how can a researcher make new inferences on the basis of synthetic output? Drawing on a synthesis of research on silicon sampling\, I discuss the intellectual foundations of this approach\, the ongoing practical and theoretical challenges\, and cutting edge methodological tools. I conclude by proposing some best practices for conducting transparent open science using large language models.\n \nValidating LLM simulations as behavioral evidence\nJessica Hullman\, Ginni Rometty Professor of Computer Science and Faculty Fellow at the Institute for Policy Research at Northwestern University.\n\nAbstract: A growing literature positions AI\, and especially large language models (LLMs)\, as a transformative technology for simulating human behavior in surveys and experiments. This promise sparks a debate over how best to leverage this new data source. While a growing number of empirical studies report that LLM-simulated responses can approximate patterns found in real survey and experimental data\, there is little consensus on what it means to show that AI surrogates are valid for the purpose of studying human behavior. I’ll contrast heuristic approaches to validation in the literature from statistical calibration approaches that account for biases learned on items for which human ground truth labels are known. While calibration approaches provide guarantees of the type that social scientists are accustomed to expecting from statistical methods\, they are not a panacea. I’ll describe limitations based on the nature of behavioral data and reflect on meta-scientific questions that arise about the epistemic status of silicon samples as behavioral data.\n\nDiscussant:  Ambuj Tewari\, Professor\, Department of Statistics\, University of Michigan\, Ann Arbor
UID:146450-21899125@events.umich.edu
URL:https://events.umich.edu/event/146450
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260318T154135
DTSTART;TZID=America/Detroit:20260408T120000
DTEND;TZID=America/Detroit:20260408T130000
SUMMARY:Lecture / Discussion:MPSDS / JPSM Seminar Series - Machine Learning for Inverse Probability Weighting in the American Community Survey
DESCRIPTION:MPSDS / JPSM Seminar Series\nMPSDS M3 Series: Mastery\, Methodology\, Meetups\n\nIn person\, room 1070\, Institute for Social Research and via Zoom. \nthe Zoom call will be locked 10 minutes after the start of the presentation. \n\nMachine Learning for Inverse Probability Weighting in the American Community Survey\n\nDeclining response rates and data collection interruptions are resulting in missing data complexity that traditional missing data techniques used in Census Bureau survey processing may not flexibly capture. At the same time\, availability and link ability of administrative records\, third party\, and previous census/survey data has improved allowing for more informative response propensity models. These developments lend themselves to the study of data-driven enhancements on inverse probability weighting (IPW) methods to adjust for unit nonresponse. We study and compare the use of traditional statistical models and machine learning algorithms applied to complex survey data for model-based IPW nonresponse adjustment using auxiliary sources with multiple years of American Community Survey data. We share various measures for model comparisons\, application-specific tuning parameter selection\, and visualizations of geographically-differentiated results.\n\nDarcy Morris is a Research Mathematical Statistician in the Center for Statistical Research and Methodology at the U.S. Census Bureau.  Dr. Morris' research interests include missing data methods for probability and nonprobability data\, categorical data analysis\, and multivariate distributions with applications in a variety of economic\, demographic\, and social topics.  She received her PhD in Statistics from Cornell University and a Master's in Statistics from George Washington University\, where she is currently a Professional Lecturer in the Data Science Program.
UID:146776-21899609@events.umich.edu
URL:https://events.umich.edu/event/146776
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location - 1070 ISR
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260513T100000
DTEND;TZID=America/Detroit:20260513T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903455@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260513T100000
DTEND;TZID=America/Detroit:20260513T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903461@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260513T130000
DTEND;TZID=America/Detroit:20260513T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903453@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260513T130000
DTEND;TZID=America/Detroit:20260513T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903522@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260514T100000
DTEND;TZID=America/Detroit:20260514T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903484@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260514T100000
DTEND;TZID=America/Detroit:20260514T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903465@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260514T130000
DTEND;TZID=America/Detroit:20260514T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903503@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260514T130000
DTEND;TZID=America/Detroit:20260514T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903523@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260515T100000
DTEND;TZID=America/Detroit:20260515T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903485@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260515T100000
DTEND;TZID=America/Detroit:20260515T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903466@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260515T130000
DTEND;TZID=America/Detroit:20260515T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903504@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260515T130000
DTEND;TZID=America/Detroit:20260515T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903524@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260516T100000
DTEND;TZID=America/Detroit:20260516T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903486@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260516T100000
DTEND;TZID=America/Detroit:20260516T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903467@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260516T130000
DTEND;TZID=America/Detroit:20260516T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903505@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260516T130000
DTEND;TZID=America/Detroit:20260516T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903525@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260517T100000
DTEND;TZID=America/Detroit:20260517T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903487@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260517T100000
DTEND;TZID=America/Detroit:20260517T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903468@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260517T130000
DTEND;TZID=America/Detroit:20260517T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903506@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260517T130000
DTEND;TZID=America/Detroit:20260517T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903526@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260518T100000
DTEND;TZID=America/Detroit:20260518T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903488@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260518T100000
DTEND;TZID=America/Detroit:20260518T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903469@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260518T130000
DTEND;TZID=America/Detroit:20260518T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903507@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260518T130000
DTEND;TZID=America/Detroit:20260518T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903527@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260519T100000
DTEND;TZID=America/Detroit:20260519T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903489@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260519T100000
DTEND;TZID=America/Detroit:20260519T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903470@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260519T130000
DTEND;TZID=America/Detroit:20260519T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903508@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260519T130000
DTEND;TZID=America/Detroit:20260519T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903528@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260520T100000
DTEND;TZID=America/Detroit:20260520T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903490@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260520T100000
DTEND;TZID=America/Detroit:20260520T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903463@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260520T100000
DTEND;TZID=America/Detroit:20260520T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903471@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260520T130000
DTEND;TZID=America/Detroit:20260520T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903509@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260520T130000
DTEND;TZID=America/Detroit:20260520T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903529@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260521T100000
DTEND;TZID=America/Detroit:20260521T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903491@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260521T100000
DTEND;TZID=America/Detroit:20260521T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903472@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260521T130000
DTEND;TZID=America/Detroit:20260521T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903510@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260521T130000
DTEND;TZID=America/Detroit:20260521T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903530@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260522T100000
DTEND;TZID=America/Detroit:20260522T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903492@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260522T100000
DTEND;TZID=America/Detroit:20260522T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903473@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260522T130000
DTEND;TZID=America/Detroit:20260522T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903511@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260522T130000
DTEND;TZID=America/Detroit:20260522T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903531@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260523T100000
DTEND;TZID=America/Detroit:20260523T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903493@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260523T100000
DTEND;TZID=America/Detroit:20260523T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903474@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260523T130000
DTEND;TZID=America/Detroit:20260523T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903512@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260523T130000
DTEND;TZID=America/Detroit:20260523T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903532@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260524T100000
DTEND;TZID=America/Detroit:20260524T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903494@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260524T100000
DTEND;TZID=America/Detroit:20260524T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903475@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260524T130000
DTEND;TZID=America/Detroit:20260524T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903513@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260524T130000
DTEND;TZID=America/Detroit:20260524T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903533@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260525T100000
DTEND;TZID=America/Detroit:20260525T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903495@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260525T100000
DTEND;TZID=America/Detroit:20260525T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903476@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260525T130000
DTEND;TZID=America/Detroit:20260525T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903514@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260525T130000
DTEND;TZID=America/Detroit:20260525T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903534@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260526T100000
DTEND;TZID=America/Detroit:20260526T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903496@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260526T100000
DTEND;TZID=America/Detroit:20260526T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903477@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260526T130000
DTEND;TZID=America/Detroit:20260526T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903515@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260526T130000
DTEND;TZID=America/Detroit:20260526T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903535@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260527T100000
DTEND;TZID=America/Detroit:20260527T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903497@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260527T100000
DTEND;TZID=America/Detroit:20260527T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903464@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260527T100000
DTEND;TZID=America/Detroit:20260527T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903478@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260527T130000
DTEND;TZID=America/Detroit:20260527T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903516@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260527T130000
DTEND;TZID=America/Detroit:20260527T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903536@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260528T100000
DTEND;TZID=America/Detroit:20260528T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903498@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260528T100000
DTEND;TZID=America/Detroit:20260528T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903479@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260528T130000
DTEND;TZID=America/Detroit:20260528T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903517@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260528T130000
DTEND;TZID=America/Detroit:20260528T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903537@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260529T100000
DTEND;TZID=America/Detroit:20260529T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903499@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260529T100000
DTEND;TZID=America/Detroit:20260529T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903480@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260529T130000
DTEND;TZID=America/Detroit:20260529T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903518@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260529T130000
DTEND;TZID=America/Detroit:20260529T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903538@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260530T100000
DTEND;TZID=America/Detroit:20260530T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903500@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260530T100000
DTEND;TZID=America/Detroit:20260530T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903481@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260530T130000
DTEND;TZID=America/Detroit:20260530T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903519@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260530T130000
DTEND;TZID=America/Detroit:20260530T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903539@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260531T100000
DTEND;TZID=America/Detroit:20260531T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903501@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260531T100000
DTEND;TZID=America/Detroit:20260531T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903482@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260531T130000
DTEND;TZID=America/Detroit:20260531T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903520@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260531T130000
DTEND;TZID=America/Detroit:20260531T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903540@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260601T100000
DTEND;TZID=America/Detroit:20260601T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903502@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260601T100000
DTEND;TZID=America/Detroit:20260601T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903483@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260601T130000
DTEND;TZID=America/Detroit:20260601T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903521@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260601T130000
DTEND;TZID=America/Detroit:20260601T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903541@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260602T100000
DTEND;TZID=America/Detroit:20260602T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903601@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260602T100000
DTEND;TZID=America/Detroit:20260602T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903614@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260602T130000
DTEND;TZID=America/Detroit:20260602T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903610@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260602T130000
DTEND;TZID=America/Detroit:20260602T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903542@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260603T100000
DTEND;TZID=America/Detroit:20260603T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903602@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260603T100000
DTEND;TZID=America/Detroit:20260603T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903615@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260603T130000
DTEND;TZID=America/Detroit:20260603T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903611@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260603T130000
DTEND;TZID=America/Detroit:20260603T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903543@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260604T100000
DTEND;TZID=America/Detroit:20260604T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903603@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260604T100000
DTEND;TZID=America/Detroit:20260604T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903616@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260604T130000
DTEND;TZID=America/Detroit:20260604T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903612@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260604T130000
DTEND;TZID=America/Detroit:20260604T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903544@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260605T100000
DTEND;TZID=America/Detroit:20260605T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903604@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260605T100000
DTEND;TZID=America/Detroit:20260605T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903617@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260605T130000
DTEND;TZID=America/Detroit:20260605T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903613@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260605T130000
DTEND;TZID=America/Detroit:20260605T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903545@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260606T100000
DTEND;TZID=America/Detroit:20260606T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903605@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260606T130000
DTEND;TZID=America/Detroit:20260606T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903546@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260607T100000
DTEND;TZID=America/Detroit:20260607T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903606@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260607T130000
DTEND;TZID=America/Detroit:20260607T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903547@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260608T100000
DTEND;TZID=America/Detroit:20260608T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903607@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260608T130000
DTEND;TZID=America/Detroit:20260608T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903548@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260609T100000
DTEND;TZID=America/Detroit:20260609T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903608@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260609T130000
DTEND;TZID=America/Detroit:20260609T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903549@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260610T100000
DTEND;TZID=America/Detroit:20260610T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903609@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260610T130000
DTEND;TZID=America/Detroit:20260610T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903550@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260611T130000
DTEND;TZID=America/Detroit:20260611T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903551@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260612T130000
DTEND;TZID=America/Detroit:20260612T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903552@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260613T130000
DTEND;TZID=America/Detroit:20260613T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903553@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260614T130000
DTEND;TZID=America/Detroit:20260614T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903554@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260615T130000
DTEND;TZID=America/Detroit:20260615T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903555@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260616T130000
DTEND;TZID=America/Detroit:20260616T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903556@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260617T130000
DTEND;TZID=America/Detroit:20260617T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903557@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260618T130000
DTEND;TZID=America/Detroit:20260618T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903558@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260619T130000
DTEND;TZID=America/Detroit:20260619T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903559@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260620T130000
DTEND;TZID=America/Detroit:20260620T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903560@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260621T130000
DTEND;TZID=America/Detroit:20260621T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903561@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260622T130000
DTEND;TZID=America/Detroit:20260622T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903562@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260623T130000
DTEND;TZID=America/Detroit:20260623T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903563@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260624T130000
DTEND;TZID=America/Detroit:20260624T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903564@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260625T130000
DTEND;TZID=America/Detroit:20260625T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903565@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260626T130000
DTEND;TZID=America/Detroit:20260626T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903566@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260627T130000
DTEND;TZID=America/Detroit:20260627T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903567@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260628T130000
DTEND;TZID=America/Detroit:20260628T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903568@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260629T130000
DTEND;TZID=America/Detroit:20260629T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903569@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260630T130000
DTEND;TZID=America/Detroit:20260630T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903570@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260701T130000
DTEND;TZID=America/Detroit:20260701T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903571@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260702T130000
DTEND;TZID=America/Detroit:20260702T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903572@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260703T130000
DTEND;TZID=America/Detroit:20260703T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903573@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260704T130000
DTEND;TZID=America/Detroit:20260704T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903574@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260705T130000
DTEND;TZID=America/Detroit:20260705T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903575@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260706T130000
DTEND;TZID=America/Detroit:20260706T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903576@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260707T130000
DTEND;TZID=America/Detroit:20260707T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903577@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260708T130000
DTEND;TZID=America/Detroit:20260708T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903578@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260709T130000
DTEND;TZID=America/Detroit:20260709T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903579@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260710T130000
DTEND;TZID=America/Detroit:20260710T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903580@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260711T130000
DTEND;TZID=America/Detroit:20260711T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903581@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260712T130000
DTEND;TZID=America/Detroit:20260712T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903582@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260713T130000
DTEND;TZID=America/Detroit:20260713T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903583@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260714T130000
DTEND;TZID=America/Detroit:20260714T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903584@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260715T130000
DTEND;TZID=America/Detroit:20260715T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903585@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260716T130000
DTEND;TZID=America/Detroit:20260716T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903586@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260717T130000
DTEND;TZID=America/Detroit:20260717T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903587@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260718T130000
DTEND;TZID=America/Detroit:20260718T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903588@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260719T130000
DTEND;TZID=America/Detroit:20260719T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903589@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260720T130000
DTEND;TZID=America/Detroit:20260720T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903590@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260721T130000
DTEND;TZID=America/Detroit:20260721T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903591@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260722T130000
DTEND;TZID=America/Detroit:20260722T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903592@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260723T130000
DTEND;TZID=America/Detroit:20260723T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903593@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260724T130000
DTEND;TZID=America/Detroit:20260724T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903594@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260725T130000
DTEND;TZID=America/Detroit:20260725T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903595@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260726T130000
DTEND;TZID=America/Detroit:20260726T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903596@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260727T130000
DTEND;TZID=America/Detroit:20260727T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903597@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260728T130000
DTEND;TZID=America/Detroit:20260728T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903598@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260729T130000
DTEND;TZID=America/Detroit:20260729T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903599@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260730T130000
DTEND;TZID=America/Detroit:20260730T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903600@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
END:VCALENDAR