Happening @ Michigan https://events.umich.edu/list/rss RSS Feed for Happening @ Michigan Events at the University of Michigan. Case Studies in Responsive Design Research in Web Surveys - Responsive Survey Design: A Research Education Program - Summer Institute in Survey Research Techniques (June 30, 2022 9:00am) https://events.umich.edu/event/95463 95463-21789948@events.umich.edu Event Begins: Thursday, June 30, 2022 9:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Case Studies in Responsive Design Research in Web Surveys

Webinar open for registration!

June 30, 2022
9:00am-1:00pm
Th

Web surveys can be an inexpensive method for collecting data. This is especially true for designs that repeat measurement over several time periods. However, these relatively low-cost data collections may result in reduced data quality if the problem of nonresponse is ignored. This webinar will examine methods for using RSD to effectively deploy scarce resources in order to minimize the risk of nonresponse bias.
Recent experiences with the University of Michigan Campus Climate Survey (UM-CCS), the National Survey of College Graduates (NSCG), and the Residential Energy Consumption Survey (RECS) are used to illustrate this point. These surveys are all defined by phased designs and multiple modes of contact. This approach improves survey outcomes, including response rates, representativeness, and cost by using alternative contact methods in later phases to recruit sample members from subgroups that were less likely to respond in earlier phases. These surveys demonstrate the benefit of RSD in web surveys across a variety of different samples sizes, and both small and large budgets and management teams. As a result, lessons from these experiences can be directly applied in many similar settings.

Not for academic credit.

Instructors: Scott Crawford & Stephanie Coffey

All 2022 courses will be held in an alternative remote format.

]]>
Class / Instruction Mon, 06 Jun 2022 16:24:56 -0400 2022-06-30T09:00:00-04:00 2022-06-30T13:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction Responsive Survey Design: A Research Education Program
Data Collection Using Wearables, Sensors, and Apps in the Social, Behavioral, and Health Sciences - Summer Institute in Survey Research Techniques (July 12, 2022 11:00am) https://events.umich.edu/event/95255 95255-21789080@events.umich.edu Event Begins: Tuesday, July 12, 2022 11:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Open for registration!

July 12 - 22, 2022
11:00am – 1:00pm EST
T & F

The 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.

Course Hour: 1

Instructors: Florian Keusch, Heidi Guyer

Prerequisite: You must have your own laptop to participate in this class.

All 2022 courses will be offered in an alternative remote format.

]]>
Class / Instruction Mon, 06 Jun 2022 10:25:32 -0400 2022-07-12T11:00:00-04:00 2022-07-12T13:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction Data Collection Using Wearables, Sensors, and Apps in the Social, Behavioral, and Health Sciences
Interventions in a Responsive Survey Design Framework-Part 2- Responsive Survey Design: A Research Education Program - Summer Institute in Survey Research Techniques (July 15, 2022 9:00am) https://events.umich.edu/event/95466 95466-21789951@events.umich.edu Event Begins: Friday, July 15, 2022 9:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Interventions in a Responsive Survey Design Framework-Part 2

Webinar open for registration!

July 15, 2022
9:00am-1:00pm
F

This second webinar in a two-part series on implementing interventions in a responsive design framework will walk participants through several real-world examples of interventions that have been applied to real surveys. Participants will also be able to work on small-group exercises designed to develop original interventions in different survey contexts.

Not for academic credit.

Instructor: Brady T. West

All 2022 courses will be held in an alternative remote format.

]]>
Class / Instruction Mon, 06 Jun 2022 16:23:34 -0400 2022-07-15T09:00:00-04:00 2022-07-15T13:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction Responsive Survey Design: A Research Education Program
Data Collection Using Wearables, Sensors, and Apps in the Social, Behavioral, and Health Sciences - Summer Institute in Survey Research Techniques (July 15, 2022 11:00am) https://events.umich.edu/event/95255 95255-21789083@events.umich.edu Event Begins: Friday, July 15, 2022 11:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Open for registration!

July 12 - 22, 2022
11:00am – 1:00pm EST
T & F

The 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.

Course Hour: 1

Instructors: Florian Keusch, Heidi Guyer

Prerequisite: You must have your own laptop to participate in this class.

All 2022 courses will be offered in an alternative remote format.

]]>
Class / Instruction Mon, 06 Jun 2022 10:25:32 -0400 2022-07-15T11:00:00-04:00 2022-07-15T13:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction Data Collection Using Wearables, Sensors, and Apps in the Social, Behavioral, and Health Sciences
Data Visualization for Active Monitoring-Part 1 - Responsive Survey Design: A Research Education Program - Summer Institute in Survey Research Techniques (July 18, 2022 9:00am) https://events.umich.edu/event/95467 95467-21789952@events.umich.edu Event Begins: Monday, July 18, 2022 9:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Data Visualization for Active Monitoring-Part 1

Webinar open for registration!

July 18, 2022
9:00am-1:00pm
M

This first webinar in a two-part webinar series on data visualization for production monitoring will cover basic concepts for the design and use of “dashboards” for monitoring survey data collection. We will begin with a detailed discussion of how to design dashboards from an RSD perspective. This will include concrete discussions of how relevant data may be collected and summarized across a variety of production environments. We will also discuss how these dashboards can be used to implement RSD interventions on an ongoing basis.

Not for academic credit.

Instructors: Brad Edwards & Victoria Vignare

All 2022 courses will be held in an alternative remote format.

]]>
Class / Instruction Mon, 06 Jun 2022 16:42:15 -0400 2022-07-18T09:00:00-04:00 2022-07-18T13:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction Responsive Survey Design: A Research Education Program
A Virtually Syntax Free Practical Introduction to Web Scraping for Survey and Social Science Researchers - Summer Institute in Survey Research Techniques (July 18, 2022 1:00pm) https://events.umich.edu/event/95709 95709-21790759@events.umich.edu Event Begins: Monday, July 18, 2022 1:00pm
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

A Virtually Syntax Free Practical Introduction to Web Scraping for Survey and Social Science Researchers

Course open for registration!

July 18-19, 2022
1:00pm-5:00pm
M/T

This short course will offer a very practical introduction to data gathering geared at social scientists and survey researchers. This course begins with an overview of web scraping discussing some basic technical jargon, types of web data and various methods for scraping. The course also includes a discussion and illustration of Application Programming Interfaces (APIs) use for gathering web data when they are available. Some websites are designed to be easily accessible by web crawlers or scraping algorithms while others require much more advanced, custom programming. And some web data can be accessed using an API that is provided by the website. In this course we will illustrate how participants can discern these differences as well as presenting several motivating examples of the various ways web scraped data can be used throughout a study’s lifecycle from design to calibration to analysis. We provide an extensive introduction to a suite of freeware programs that allow virtually syntax free, but customizable, web scraping capabilities. We contrast this type of gathered data access to APIs for some websites like Zillow or Twitter and discuss pros and cons of using web scraping or APIs to gather this type of web data. The course concludes with specific focus on the import.io tool where we demonstrate its capabilities and provide several, hands-on practical examples for participants to begin scraping several websites of increasing complexity. We will also illustrate API calls in R for Zillow, the Census and others as time permits.

Not for academic credit.

Instructor: Trent Buskirk

All 2022 courses will be held in an alternative remote format.

]]>
Class / Instruction Mon, 20 Jun 2022 13:50:13 -0400 2022-07-18T13:00:00-04:00 2022-07-18T17:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction A Virtually Syntax Free Practical Introduction to Web Scraping for Survey and Social Science Researchers
Data Collection Using Wearables, Sensors, and Apps in the Social, Behavioral, and Health Sciences - Summer Institute in Survey Research Techniques (July 19, 2022 11:00am) https://events.umich.edu/event/95255 95255-21789087@events.umich.edu Event Begins: Tuesday, July 19, 2022 11:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Open for registration!

July 12 - 22, 2022
11:00am – 1:00pm EST
T & F

The 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.

Course Hour: 1

Instructors: Florian Keusch, Heidi Guyer

Prerequisite: You must have your own laptop to participate in this class.

All 2022 courses will be offered in an alternative remote format.

]]>
Class / Instruction Mon, 06 Jun 2022 10:25:32 -0400 2022-07-19T11:00:00-04:00 2022-07-19T13:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction Data Collection Using Wearables, Sensors, and Apps in the Social, Behavioral, and Health Sciences
A Virtually Syntax Free Practical Introduction to Web Scraping for Survey and Social Science Researchers - Summer Institute in Survey Research Techniques (July 19, 2022 1:00pm) https://events.umich.edu/event/95709 95709-21790760@events.umich.edu Event Begins: Tuesday, July 19, 2022 1:00pm
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

A Virtually Syntax Free Practical Introduction to Web Scraping for Survey and Social Science Researchers

Course open for registration!

July 18-19, 2022
1:00pm-5:00pm
M/T

This short course will offer a very practical introduction to data gathering geared at social scientists and survey researchers. This course begins with an overview of web scraping discussing some basic technical jargon, types of web data and various methods for scraping. The course also includes a discussion and illustration of Application Programming Interfaces (APIs) use for gathering web data when they are available. Some websites are designed to be easily accessible by web crawlers or scraping algorithms while others require much more advanced, custom programming. And some web data can be accessed using an API that is provided by the website. In this course we will illustrate how participants can discern these differences as well as presenting several motivating examples of the various ways web scraped data can be used throughout a study’s lifecycle from design to calibration to analysis. We provide an extensive introduction to a suite of freeware programs that allow virtually syntax free, but customizable, web scraping capabilities. We contrast this type of gathered data access to APIs for some websites like Zillow or Twitter and discuss pros and cons of using web scraping or APIs to gather this type of web data. The course concludes with specific focus on the import.io tool where we demonstrate its capabilities and provide several, hands-on practical examples for participants to begin scraping several websites of increasing complexity. We will also illustrate API calls in R for Zillow, the Census and others as time permits.

Not for academic credit.

Instructor: Trent Buskirk

All 2022 courses will be held in an alternative remote format.

]]>
Class / Instruction Mon, 20 Jun 2022 13:50:13 -0400 2022-07-19T13:00:00-04:00 2022-07-19T17:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction A Virtually Syntax Free Practical Introduction to Web Scraping for Survey and Social Science Researchers
Using the Health and Retirement Study for Research on Aging in the United States (July 19, 2022 7:30pm) https://events.umich.edu/event/95974 95974-21791512@events.umich.edu Event Begins: Tuesday, July 19, 2022 7:30pm
Location: Off Campus Location
Organized By: Inter-university Consortium for Political and Social Research

Join us for this virtual lecture from the 2022 Blalock Lecture Series from the ICPSR Summer Program in Quantitative Methods of Social Science.

The 2022 Blalock Lecture Series includes 17 lectures on social science topics and data. Completely virtual, free, and open to the public. All lectures will be held from 7:30-9:00 pm ET. Share freely with friends and colleagues.

Find the full list of 2022 Blalock Lectures at https://myumi.ch/ICPSR2022Blalocks.

]]>
Lecture / Discussion Thu, 07 Jul 2022 19:44:16 -0400 2022-07-19T19:30:00-04:00 2022-07-19T21:00:00-04:00 Off Campus Location Inter-university Consortium for Political and Social Research Lecture / Discussion Using the Health and Retirement Study for Research on Aging in the United States - ICPSR Blalock Lecture Series 2022
Data Visualization for Active Monitoring-Part 2 - Responsive Survey Design: A Research Education Program - Summer Institute in Survey Research Techniques (July 20, 2022 9:00am) https://events.umich.edu/event/95468 95468-21789953@events.umich.edu Event Begins: Wednesday, July 20, 2022 9:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Data Visualization for Active Monitoring-Part 2

Webinar open for registration!

July 20, 2022
9:00am-1:00pm
W

This second webinar in a two-part webinar series on data visualization for production monitoring will demonstrate concepts from the first webinar using examples from actual dashboards. We will briefly explore methods for modeling incoming paradata in order to detect outliers. We will then consider practical issues associated with the development of dashboards, including software alternatives. Finally, we will demonstrate how to update dashboards using data reflecting the results of ongoing fieldwork. Participants will be provided with template spreadsheet dashboards for their own applications.

Not for academic credit.

Instructors: Brad Edwards & Victoria Vignare

All 2022 courses will be held in an alternative remote format.

]]>
Class / Instruction Mon, 06 Jun 2022 16:41:12 -0400 2022-07-20T09:00:00-04:00 2022-07-20T13:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction Responsive Survey Design: A Research Education Program
An Introduction to Big Data and Machine Learning for Survey Researchers and Social Scientists - Summer Institute in Survey Research Techniques (July 20, 2022 1:00pm) https://events.umich.edu/event/95710 95710-21790763@events.umich.edu Event Begins: Wednesday, July 20, 2022 1:00pm
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

An Introduction to Big Data and Machine Learning for Survey Researchers and Social Scientists

Course open for registration!
Open to all!

July 20-22, 2022
1:00pm – 5:00pm
M/Th/F

The amount of data generated as a by-product in society is growing fast including data from satellites, sensors, transactions, social media and smartphones, just to name a few. Such data are often referred to as “big data”, and can be used to create value in different areas such as health and crime prevention, commerce and fraud detection. An emerging practice in many areas is to append or link big data sources with more specific and smaller scale sources that often contain much more limited information. This practice has been used for some time by survey researchers in constructing frames by appending auxiliary information that is often not directly available on the frame, but can be obtained from an external source. Using Big Data has the potential to go beyond the sampling phase for survey researchers and in fact has the potential to influence the social sciences in general. Big Data is of interest for public opinion researchers and agencies that produce statistics to find alternative data sources either to reduce costs, to improve estimates or to produce estimates in a more timely fashion. However, Big Data pose several interesting and new challenges to survey researchers and social scientists among others who want to extract information from data. As Robert Groves (2012) pointedly commented, the era is “appropriately called Big Data and not Big Information”, because there is a lot of work for analysts before information can be gained from “auxiliary traces of some process that is going on in society.”

This course offers participants a broad overview of big data sources, opportunities and examples motivated within the survey and social science contexts including the use of social media data, para data and other such sources. This course also offers a detailed, practical introduction to four common machine learning methods that can be applied to big and small data alike at various aspects of a study’s lifecycle from design to nonresponse adjustments to propensity score matching to weighting and evaluation and analysis. The machine learning methods will be demonstrated in R and we will provide several different examples of using these methods along with multiple packages in R that offer these methods.

Not for academic credit

Instructor: Trent Buskirk

All 2022 courses will be held in an alternative remote format.

]]>
Class / Instruction Mon, 20 Jun 2022 14:06:23 -0400 2022-07-20T13:00:00-04:00 2022-07-20T17:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction An Introduction to Big Data and Machine Learning for Survey Researchers and Social Scientists
An Introduction to Big Data and Machine Learning for Survey Researchers and Social Scientists - Summer Institute in Survey Research Techniques (July 21, 2022 1:00pm) https://events.umich.edu/event/95710 95710-21790764@events.umich.edu Event Begins: Thursday, July 21, 2022 1:00pm
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

An Introduction to Big Data and Machine Learning for Survey Researchers and Social Scientists

Course open for registration!
Open to all!

July 20-22, 2022
1:00pm – 5:00pm
M/Th/F

The amount of data generated as a by-product in society is growing fast including data from satellites, sensors, transactions, social media and smartphones, just to name a few. Such data are often referred to as “big data”, and can be used to create value in different areas such as health and crime prevention, commerce and fraud detection. An emerging practice in many areas is to append or link big data sources with more specific and smaller scale sources that often contain much more limited information. This practice has been used for some time by survey researchers in constructing frames by appending auxiliary information that is often not directly available on the frame, but can be obtained from an external source. Using Big Data has the potential to go beyond the sampling phase for survey researchers and in fact has the potential to influence the social sciences in general. Big Data is of interest for public opinion researchers and agencies that produce statistics to find alternative data sources either to reduce costs, to improve estimates or to produce estimates in a more timely fashion. However, Big Data pose several interesting and new challenges to survey researchers and social scientists among others who want to extract information from data. As Robert Groves (2012) pointedly commented, the era is “appropriately called Big Data and not Big Information”, because there is a lot of work for analysts before information can be gained from “auxiliary traces of some process that is going on in society.”

This course offers participants a broad overview of big data sources, opportunities and examples motivated within the survey and social science contexts including the use of social media data, para data and other such sources. This course also offers a detailed, practical introduction to four common machine learning methods that can be applied to big and small data alike at various aspects of a study’s lifecycle from design to nonresponse adjustments to propensity score matching to weighting and evaluation and analysis. The machine learning methods will be demonstrated in R and we will provide several different examples of using these methods along with multiple packages in R that offer these methods.

Not for academic credit

Instructor: Trent Buskirk

All 2022 courses will be held in an alternative remote format.

]]>
Class / Instruction Mon, 20 Jun 2022 14:06:23 -0400 2022-07-21T13:00:00-04:00 2022-07-21T17:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction An Introduction to Big Data and Machine Learning for Survey Researchers and Social Scientists
HIPAA: protection and use of US health information (July 21, 2022 7:30pm) https://events.umich.edu/event/95975 95975-21791513@events.umich.edu Event Begins: Thursday, July 21, 2022 7:30pm
Location: Off Campus Location
Organized By: Inter-university Consortium for Political and Social Research

Join us for this virtual lecture from the 2022 Blalock Lecture Series from the ICPSR Summer Program in Quantitative Methods of Social Science.

The 2022 Blalock Lecture Series includes 17 lectures on social science topics and data. Completely virtual, free, and open to the public. All lectures will be held from 7:30-9:00 pm ET. Share freely with friends and colleagues.

Find the full list of 2022 Blalock Lectures at https://myumi.ch/ICPSR2022Blalocks.

]]>
Lecture / Discussion Thu, 07 Jul 2022 19:50:14 -0400 2022-07-21T19:30:00-04:00 2022-07-21T21:00:00-04:00 Off Campus Location Inter-university Consortium for Political and Social Research Lecture / Discussion HIPAA: protection and use of US health information - ICPSR Summer Program in Quantitative Methods of Social Science Blalock Lecture Series 2022
Data Collection Using Wearables, Sensors, and Apps in the Social, Behavioral, and Health Sciences - Summer Institute in Survey Research Techniques (July 22, 2022 11:00am) https://events.umich.edu/event/95255 95255-21789090@events.umich.edu Event Begins: Friday, July 22, 2022 11:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Open for registration!

July 12 - 22, 2022
11:00am – 1:00pm EST
T & F

The 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.

Course Hour: 1

Instructors: Florian Keusch, Heidi Guyer

Prerequisite: You must have your own laptop to participate in this class.

All 2022 courses will be offered in an alternative remote format.

]]>
Class / Instruction Mon, 06 Jun 2022 10:25:32 -0400 2022-07-22T11:00:00-04:00 2022-07-22T13:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction Data Collection Using Wearables, Sensors, and Apps in the Social, Behavioral, and Health Sciences
An Introduction to Big Data and Machine Learning for Survey Researchers and Social Scientists - Summer Institute in Survey Research Techniques (July 22, 2022 1:00pm) https://events.umich.edu/event/95710 95710-21790765@events.umich.edu Event Begins: Friday, July 22, 2022 1:00pm
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

An Introduction to Big Data and Machine Learning for Survey Researchers and Social Scientists

Course open for registration!
Open to all!

July 20-22, 2022
1:00pm – 5:00pm
M/Th/F

The amount of data generated as a by-product in society is growing fast including data from satellites, sensors, transactions, social media and smartphones, just to name a few. Such data are often referred to as “big data”, and can be used to create value in different areas such as health and crime prevention, commerce and fraud detection. An emerging practice in many areas is to append or link big data sources with more specific and smaller scale sources that often contain much more limited information. This practice has been used for some time by survey researchers in constructing frames by appending auxiliary information that is often not directly available on the frame, but can be obtained from an external source. Using Big Data has the potential to go beyond the sampling phase for survey researchers and in fact has the potential to influence the social sciences in general. Big Data is of interest for public opinion researchers and agencies that produce statistics to find alternative data sources either to reduce costs, to improve estimates or to produce estimates in a more timely fashion. However, Big Data pose several interesting and new challenges to survey researchers and social scientists among others who want to extract information from data. As Robert Groves (2012) pointedly commented, the era is “appropriately called Big Data and not Big Information”, because there is a lot of work for analysts before information can be gained from “auxiliary traces of some process that is going on in society.”

This course offers participants a broad overview of big data sources, opportunities and examples motivated within the survey and social science contexts including the use of social media data, para data and other such sources. This course also offers a detailed, practical introduction to four common machine learning methods that can be applied to big and small data alike at various aspects of a study’s lifecycle from design to nonresponse adjustments to propensity score matching to weighting and evaluation and analysis. The machine learning methods will be demonstrated in R and we will provide several different examples of using these methods along with multiple packages in R that offer these methods.

Not for academic credit

Instructor: Trent Buskirk

All 2022 courses will be held in an alternative remote format.

]]>
Class / Instruction Mon, 20 Jun 2022 14:06:23 -0400 2022-07-22T13:00:00-04:00 2022-07-22T17:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction An Introduction to Big Data and Machine Learning for Survey Researchers and Social Scientists
Design and Implementation of Web Surveys - Summer Institute in Survey Research Techniques (July 25, 2022 9:00am) https://events.umich.edu/event/95712 95712-21790769@events.umich.edu Event Begins: Monday, July 25, 2022 9:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Design and Implementation of Web Surveys

Course open for registration!
Open to all!

July 25-29, 2022
9:00am-1:00pm,
M/T/W/Th/F

his one-week course introduces students to the design and implementation of online survey data collection instruments. The course is both hands-on and conceptual. It begins by discussing what is unique about web surveys and when their use is most appropriate, followed by an introduction to survey errors that can affect the quality of web survey data. Small groups of students will each develop a research problem and a questionnaire to address their problem, designed for online administration. They will pretest the question wording, program the questionnaire using a web survey development platform (no programming experience is required), and assess users’ (respondents’) experience while interacting with the web-based instrument. Students will also develop basic plans for data collection and analysis. Finally, each group will present its problem, online questionnaire, evaluation, and plans to the rest of the class.

Why take this course?

· To gain an understanding of what should go into creating a web-based questionnaire

· To gain experience weighing the pros and cons of different web questionnaire features

· To gain experience building a web questionnaire on a standard platform

· To gain experience evaluating survey questions and their usability in an online questionnaire

Not for academic credit

Instructors: Frederick Conrad, Florian Keusch and Christopher Antoun

All 2022 courses will we held in an alternative remote format.
,

]]>
Class / Instruction Mon, 20 Jun 2022 14:26:09 -0400 2022-07-25T09:00:00-04:00 2022-07-25T13:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction Design and Implementation of Web Surveys
Design and Implementation of Web Surveys - Summer Institute in Survey Research Techniques (July 26, 2022 9:00am) https://events.umich.edu/event/95712 95712-21790770@events.umich.edu Event Begins: Tuesday, July 26, 2022 9:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Design and Implementation of Web Surveys

Course open for registration!
Open to all!

July 25-29, 2022
9:00am-1:00pm,
M/T/W/Th/F

his one-week course introduces students to the design and implementation of online survey data collection instruments. The course is both hands-on and conceptual. It begins by discussing what is unique about web surveys and when their use is most appropriate, followed by an introduction to survey errors that can affect the quality of web survey data. Small groups of students will each develop a research problem and a questionnaire to address their problem, designed for online administration. They will pretest the question wording, program the questionnaire using a web survey development platform (no programming experience is required), and assess users’ (respondents’) experience while interacting with the web-based instrument. Students will also develop basic plans for data collection and analysis. Finally, each group will present its problem, online questionnaire, evaluation, and plans to the rest of the class.

Why take this course?

· To gain an understanding of what should go into creating a web-based questionnaire

· To gain experience weighing the pros and cons of different web questionnaire features

· To gain experience building a web questionnaire on a standard platform

· To gain experience evaluating survey questions and their usability in an online questionnaire

Not for academic credit

Instructors: Frederick Conrad, Florian Keusch and Christopher Antoun

All 2022 courses will we held in an alternative remote format.
,

]]>
Class / Instruction Mon, 20 Jun 2022 14:26:09 -0400 2022-07-26T09:00:00-04:00 2022-07-26T13:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction Design and Implementation of Web Surveys
Design and Implementation of Web Surveys - Summer Institute in Survey Research Techniques (July 27, 2022 9:00am) https://events.umich.edu/event/95712 95712-21790771@events.umich.edu Event Begins: Wednesday, July 27, 2022 9:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Design and Implementation of Web Surveys

Course open for registration!
Open to all!

July 25-29, 2022
9:00am-1:00pm,
M/T/W/Th/F

his one-week course introduces students to the design and implementation of online survey data collection instruments. The course is both hands-on and conceptual. It begins by discussing what is unique about web surveys and when their use is most appropriate, followed by an introduction to survey errors that can affect the quality of web survey data. Small groups of students will each develop a research problem and a questionnaire to address their problem, designed for online administration. They will pretest the question wording, program the questionnaire using a web survey development platform (no programming experience is required), and assess users’ (respondents’) experience while interacting with the web-based instrument. Students will also develop basic plans for data collection and analysis. Finally, each group will present its problem, online questionnaire, evaluation, and plans to the rest of the class.

Why take this course?

· To gain an understanding of what should go into creating a web-based questionnaire

· To gain experience weighing the pros and cons of different web questionnaire features

· To gain experience building a web questionnaire on a standard platform

· To gain experience evaluating survey questions and their usability in an online questionnaire

Not for academic credit

Instructors: Frederick Conrad, Florian Keusch and Christopher Antoun

All 2022 courses will we held in an alternative remote format.
,

]]>
Class / Instruction Mon, 20 Jun 2022 14:26:09 -0400 2022-07-27T09:00:00-04:00 2022-07-27T13:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction Design and Implementation of Web Surveys
Design and Implementation of Web Surveys - Summer Institute in Survey Research Techniques (July 28, 2022 9:00am) https://events.umich.edu/event/95712 95712-21790772@events.umich.edu Event Begins: Thursday, July 28, 2022 9:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Design and Implementation of Web Surveys

Course open for registration!
Open to all!

July 25-29, 2022
9:00am-1:00pm,
M/T/W/Th/F

his one-week course introduces students to the design and implementation of online survey data collection instruments. The course is both hands-on and conceptual. It begins by discussing what is unique about web surveys and when their use is most appropriate, followed by an introduction to survey errors that can affect the quality of web survey data. Small groups of students will each develop a research problem and a questionnaire to address their problem, designed for online administration. They will pretest the question wording, program the questionnaire using a web survey development platform (no programming experience is required), and assess users’ (respondents’) experience while interacting with the web-based instrument. Students will also develop basic plans for data collection and analysis. Finally, each group will present its problem, online questionnaire, evaluation, and plans to the rest of the class.

Why take this course?

· To gain an understanding of what should go into creating a web-based questionnaire

· To gain experience weighing the pros and cons of different web questionnaire features

· To gain experience building a web questionnaire on a standard platform

· To gain experience evaluating survey questions and their usability in an online questionnaire

Not for academic credit

Instructors: Frederick Conrad, Florian Keusch and Christopher Antoun

All 2022 courses will we held in an alternative remote format.
,

]]>
Class / Instruction Mon, 20 Jun 2022 14:26:09 -0400 2022-07-28T09:00:00-04:00 2022-07-28T13:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction Design and Implementation of Web Surveys
Design and Implementation of Web Surveys - Summer Institute in Survey Research Techniques (July 29, 2022 9:00am) https://events.umich.edu/event/95712 95712-21790773@events.umich.edu Event Begins: Friday, July 29, 2022 9:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Design and Implementation of Web Surveys

Course open for registration!
Open to all!

July 25-29, 2022
9:00am-1:00pm,
M/T/W/Th/F

his one-week course introduces students to the design and implementation of online survey data collection instruments. The course is both hands-on and conceptual. It begins by discussing what is unique about web surveys and when their use is most appropriate, followed by an introduction to survey errors that can affect the quality of web survey data. Small groups of students will each develop a research problem and a questionnaire to address their problem, designed for online administration. They will pretest the question wording, program the questionnaire using a web survey development platform (no programming experience is required), and assess users’ (respondents’) experience while interacting with the web-based instrument. Students will also develop basic plans for data collection and analysis. Finally, each group will present its problem, online questionnaire, evaluation, and plans to the rest of the class.

Why take this course?

· To gain an understanding of what should go into creating a web-based questionnaire

· To gain experience weighing the pros and cons of different web questionnaire features

· To gain experience building a web questionnaire on a standard platform

· To gain experience evaluating survey questions and their usability in an online questionnaire

Not for academic credit

Instructors: Frederick Conrad, Florian Keusch and Christopher Antoun

All 2022 courses will we held in an alternative remote format.
,

]]>
Class / Instruction Mon, 20 Jun 2022 14:26:09 -0400 2022-07-29T09:00:00-04:00 2022-07-29T13:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction Design and Implementation of Web Surveys
The New NIH Data Sharing Policy (August 2, 2022 7:30pm) https://events.umich.edu/event/95979 95979-21791517@events.umich.edu Event Begins: Tuesday, August 2, 2022 7:30pm
Location: Off Campus Location
Organized By: Inter-university Consortium for Political and Social Research

Join us for this virtual lecture from the 2022 Blalock Lecture Series from the ICPSR Summer Program in Quantitative Methods of Social Science.

The 2022 Blalock Lecture Series includes 17 lectures on social science topics and data. Completely virtual, free, and open to the public. All lectures will be held from 7:30-9:00 pm ET. Share freely with friends and colleagues.

Find the full list of 2022 Blalock Lectures at https://myumi.ch/ICPSR2022Blalocks.

]]>
Lecture / Discussion Thu, 07 Jul 2022 20:29:19 -0400 2022-08-02T19:30:00-04:00 2022-08-02T21:00:00-04:00 Off Campus Location Inter-university Consortium for Political and Social Research Lecture / Discussion The New NIH Data Sharing Policy - ICPSR Summer Program in Quantitative Methods of Social Science Blalock Lecture Series 2022
Code-Free Machine Learning: Introduction to Concepts and Best Practices with Hands-on Experiences - Summer Institute in Survey Research Techniques (September 7, 2022 10:00am) https://events.umich.edu/event/95713 95713-21790774@events.umich.edu Event Begins: Wednesday, September 7, 2022 10:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Code-Free Machine Learning: Introduction to Concepts and Best Practices with Hands-on Experiences

Course open for registration!
Open to all!

September 7 - October 5, 2022
10:00am-12:00pm
Wednesdays

Social scientists are increasingly interested in machine learning methods to glean scientific knowledge and actionable insights from designed and gathered data. Implementing machine learning, however, requires users to have programming skills. This can be a daunting challenge for many non-tech savvy researchers. This course aims to guide social scientists to explore how machine learning can be used for their research without learning how to code. This course uses a graphical user interface tool Orange to provide learners with hands-on experiences in implementing machine learning techniques including data cleaning, visualization, and fine-tuning of algorithmic models. The open-source tool Orange is built on popular Python packages, providing basically the same functions and performances as many data scientists would obtain by writing complicated code. The course demonstrates that researchers can utilize the power of machine learning without learning how to code and focus more on machine learning concepts and best practices as well as analytical model development and validation.

Prerequisite: You must have your own laptop or desktop with Orange installed to participate in this class. For installation instruction of Orange, see https://orangedatamining.com/

Not for academic credit.

Instructor: Jinseok Kim

All 2022 courses will be held in an alternative format.

]]>
Class / Instruction Mon, 20 Jun 2022 14:53:44 -0400 2022-09-07T10:00:00-04:00 2022-09-07T12:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction
Code-Free Machine Learning: Introduction to Concepts and Best Practices with Hands-on Experiences - Summer Institute in Survey Research Techniques (September 14, 2022 10:00am) https://events.umich.edu/event/95713 95713-21790775@events.umich.edu Event Begins: Wednesday, September 14, 2022 10:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Code-Free Machine Learning: Introduction to Concepts and Best Practices with Hands-on Experiences

Course open for registration!
Open to all!

September 7 - October 5, 2022
10:00am-12:00pm
Wednesdays

Social scientists are increasingly interested in machine learning methods to glean scientific knowledge and actionable insights from designed and gathered data. Implementing machine learning, however, requires users to have programming skills. This can be a daunting challenge for many non-tech savvy researchers. This course aims to guide social scientists to explore how machine learning can be used for their research without learning how to code. This course uses a graphical user interface tool Orange to provide learners with hands-on experiences in implementing machine learning techniques including data cleaning, visualization, and fine-tuning of algorithmic models. The open-source tool Orange is built on popular Python packages, providing basically the same functions and performances as many data scientists would obtain by writing complicated code. The course demonstrates that researchers can utilize the power of machine learning without learning how to code and focus more on machine learning concepts and best practices as well as analytical model development and validation.

Prerequisite: You must have your own laptop or desktop with Orange installed to participate in this class. For installation instruction of Orange, see https://orangedatamining.com/

Not for academic credit.

Instructor: Jinseok Kim

All 2022 courses will be held in an alternative format.

]]>
Class / Instruction Mon, 20 Jun 2022 14:53:44 -0400 2022-09-14T10:00:00-04:00 2022-09-14T12:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction
ICPSR Data Fair - a free virtual data conference (September 19, 2022 10:00am) https://events.umich.edu/event/97433 97433-21794559@events.umich.edu Event Begins: Monday, September 19, 2022 10:00am
Location: Off Campus Location
Organized By: Inter-university Consortium for Political and Social Research

ICPSR (the world's largest social science data archive) is hosting the Data Fair, offering tools and inspiration for the global data community. Featuring 20+ virtual presentations on data and resources. Presentation topics include COVID data, criminal justice, economics, health care, drug use, sociology, data visualizations, and more. All presentations will be 30 minutes or less!

Please spread the word. The Data Fair is completely free, open to the public, and takes place entirely online.

When: September 19-23, 2022
Where: Online
Who’s invited: Open to the public
Register at https://myumi.ch/ICPSRDataFair2022

]]>
Conference / Symposium Thu, 25 Aug 2022 13:38:37 -0400 2022-09-19T10:00:00-04:00 2022-09-19T16:00:00-04:00 Off Campus Location Inter-university Consortium for Political and Social Research Conference / Symposium ICPSR Data Fair 2022 image with a hand holding a deconstructed globe on a green background
ICPSR Data Fair - a free virtual data conference (September 20, 2022 10:00am) https://events.umich.edu/event/97433 97433-21794560@events.umich.edu Event Begins: Tuesday, September 20, 2022 10:00am
Location: Off Campus Location
Organized By: Inter-university Consortium for Political and Social Research

ICPSR (the world's largest social science data archive) is hosting the Data Fair, offering tools and inspiration for the global data community. Featuring 20+ virtual presentations on data and resources. Presentation topics include COVID data, criminal justice, economics, health care, drug use, sociology, data visualizations, and more. All presentations will be 30 minutes or less!

Please spread the word. The Data Fair is completely free, open to the public, and takes place entirely online.

When: September 19-23, 2022
Where: Online
Who’s invited: Open to the public
Register at https://myumi.ch/ICPSRDataFair2022

]]>
Conference / Symposium Thu, 25 Aug 2022 13:38:37 -0400 2022-09-20T10:00:00-04:00 2022-09-20T16:00:00-04:00 Off Campus Location Inter-university Consortium for Political and Social Research Conference / Symposium ICPSR Data Fair 2022 image with a hand holding a deconstructed globe on a green background
Code-Free Machine Learning: Introduction to Concepts and Best Practices with Hands-on Experiences - Summer Institute in Survey Research Techniques (September 21, 2022 10:00am) https://events.umich.edu/event/95713 95713-21790776@events.umich.edu Event Begins: Wednesday, September 21, 2022 10:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Code-Free Machine Learning: Introduction to Concepts and Best Practices with Hands-on Experiences

Course open for registration!
Open to all!

September 7 - October 5, 2022
10:00am-12:00pm
Wednesdays

Social scientists are increasingly interested in machine learning methods to glean scientific knowledge and actionable insights from designed and gathered data. Implementing machine learning, however, requires users to have programming skills. This can be a daunting challenge for many non-tech savvy researchers. This course aims to guide social scientists to explore how machine learning can be used for their research without learning how to code. This course uses a graphical user interface tool Orange to provide learners with hands-on experiences in implementing machine learning techniques including data cleaning, visualization, and fine-tuning of algorithmic models. The open-source tool Orange is built on popular Python packages, providing basically the same functions and performances as many data scientists would obtain by writing complicated code. The course demonstrates that researchers can utilize the power of machine learning without learning how to code and focus more on machine learning concepts and best practices as well as analytical model development and validation.

Prerequisite: You must have your own laptop or desktop with Orange installed to participate in this class. For installation instruction of Orange, see https://orangedatamining.com/

Not for academic credit.

Instructor: Jinseok Kim

All 2022 courses will be held in an alternative format.

]]>
Class / Instruction Mon, 20 Jun 2022 14:53:44 -0400 2022-09-21T10:00:00-04:00 2022-09-21T12:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction
ICPSR Data Fair - a free virtual data conference (September 21, 2022 10:00am) https://events.umich.edu/event/97433 97433-21794561@events.umich.edu Event Begins: Wednesday, September 21, 2022 10:00am
Location: Off Campus Location
Organized By: Inter-university Consortium for Political and Social Research

ICPSR (the world's largest social science data archive) is hosting the Data Fair, offering tools and inspiration for the global data community. Featuring 20+ virtual presentations on data and resources. Presentation topics include COVID data, criminal justice, economics, health care, drug use, sociology, data visualizations, and more. All presentations will be 30 minutes or less!

Please spread the word. The Data Fair is completely free, open to the public, and takes place entirely online.

When: September 19-23, 2022
Where: Online
Who’s invited: Open to the public
Register at https://myumi.ch/ICPSRDataFair2022

]]>
Conference / Symposium Thu, 25 Aug 2022 13:38:37 -0400 2022-09-21T10:00:00-04:00 2022-09-21T16:00:00-04:00 Off Campus Location Inter-university Consortium for Political and Social Research Conference / Symposium ICPSR Data Fair 2022 image with a hand holding a deconstructed globe on a green background
Data Collection Using Wearables, Sensors, and Apps in the Social, Behavioral, and Health Sciences - Summer Institute in Survey Research Techniques (September 21, 2022 11:00am) https://events.umich.edu/event/95724 95724-21790794@events.umich.edu Event Begins: Wednesday, September 21, 2022 11:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Data Collection Using Wearables, Sensors, and Apps in the Social, Behavioral, and Health Sciences

Course open for registration!
Open to all!

September 21-30, 2022
11:00am-1:00pm
Wednesdays and Fridays

The 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.

Not for academic credit.

Instructors: Florian Keusch and Heidi Guyer

All 2022 courses will be held in an alternative remote format.

]]>
Class / Instruction Wed, 22 Jun 2022 11:44:43 -0400 2022-09-21T11:00:00-04:00 2022-09-21T13:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction
ICPSR Data Fair - a free virtual data conference (September 22, 2022 10:00am) https://events.umich.edu/event/97433 97433-21794562@events.umich.edu Event Begins: Thursday, September 22, 2022 10:00am
Location: Off Campus Location
Organized By: Inter-university Consortium for Political and Social Research

ICPSR (the world's largest social science data archive) is hosting the Data Fair, offering tools and inspiration for the global data community. Featuring 20+ virtual presentations on data and resources. Presentation topics include COVID data, criminal justice, economics, health care, drug use, sociology, data visualizations, and more. All presentations will be 30 minutes or less!

Please spread the word. The Data Fair is completely free, open to the public, and takes place entirely online.

When: September 19-23, 2022
Where: Online
Who’s invited: Open to the public
Register at https://myumi.ch/ICPSRDataFair2022

]]>
Conference / Symposium Thu, 25 Aug 2022 13:38:37 -0400 2022-09-22T10:00:00-04:00 2022-09-22T16:00:00-04:00 Off Campus Location Inter-university Consortium for Political and Social Research Conference / Symposium ICPSR Data Fair 2022 image with a hand holding a deconstructed globe on a green background
ICPSR Data Fair - a free virtual data conference (September 23, 2022 10:00am) https://events.umich.edu/event/97433 97433-21794563@events.umich.edu Event Begins: Friday, September 23, 2022 10:00am
Location: Off Campus Location
Organized By: Inter-university Consortium for Political and Social Research

ICPSR (the world's largest social science data archive) is hosting the Data Fair, offering tools and inspiration for the global data community. Featuring 20+ virtual presentations on data and resources. Presentation topics include COVID data, criminal justice, economics, health care, drug use, sociology, data visualizations, and more. All presentations will be 30 minutes or less!

Please spread the word. The Data Fair is completely free, open to the public, and takes place entirely online.

When: September 19-23, 2022
Where: Online
Who’s invited: Open to the public
Register at https://myumi.ch/ICPSRDataFair2022

]]>
Conference / Symposium Thu, 25 Aug 2022 13:38:37 -0400 2022-09-23T10:00:00-04:00 2022-09-23T16:00:00-04:00 Off Campus Location Inter-university Consortium for Political and Social Research Conference / Symposium ICPSR Data Fair 2022 image with a hand holding a deconstructed globe on a green background
Data Collection Using Wearables, Sensors, and Apps in the Social, Behavioral, and Health Sciences - Summer Institute in Survey Research Techniques (September 23, 2022 11:00am) https://events.umich.edu/event/95724 95724-21790796@events.umich.edu Event Begins: Friday, September 23, 2022 11:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Data Collection Using Wearables, Sensors, and Apps in the Social, Behavioral, and Health Sciences

Course open for registration!
Open to all!

September 21-30, 2022
11:00am-1:00pm
Wednesdays and Fridays

The 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.

Not for academic credit.

Instructors: Florian Keusch and Heidi Guyer

All 2022 courses will be held in an alternative remote format.

]]>
Class / Instruction Wed, 22 Jun 2022 11:44:43 -0400 2022-09-23T11:00:00-04:00 2022-09-23T13:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction
Code-Free Machine Learning: Introduction to Concepts and Best Practices with Hands-on Experiences - Summer Institute in Survey Research Techniques (September 28, 2022 10:00am) https://events.umich.edu/event/95713 95713-21790777@events.umich.edu Event Begins: Wednesday, September 28, 2022 10:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Code-Free Machine Learning: Introduction to Concepts and Best Practices with Hands-on Experiences

Course open for registration!
Open to all!

September 7 - October 5, 2022
10:00am-12:00pm
Wednesdays

Social scientists are increasingly interested in machine learning methods to glean scientific knowledge and actionable insights from designed and gathered data. Implementing machine learning, however, requires users to have programming skills. This can be a daunting challenge for many non-tech savvy researchers. This course aims to guide social scientists to explore how machine learning can be used for their research without learning how to code. This course uses a graphical user interface tool Orange to provide learners with hands-on experiences in implementing machine learning techniques including data cleaning, visualization, and fine-tuning of algorithmic models. The open-source tool Orange is built on popular Python packages, providing basically the same functions and performances as many data scientists would obtain by writing complicated code. The course demonstrates that researchers can utilize the power of machine learning without learning how to code and focus more on machine learning concepts and best practices as well as analytical model development and validation.

Prerequisite: You must have your own laptop or desktop with Orange installed to participate in this class. For installation instruction of Orange, see https://orangedatamining.com/

Not for academic credit.

Instructor: Jinseok Kim

All 2022 courses will be held in an alternative format.

]]>
Class / Instruction Mon, 20 Jun 2022 14:53:44 -0400 2022-09-28T10:00:00-04:00 2022-09-28T12:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction
Data Collection Using Wearables, Sensors, and Apps in the Social, Behavioral, and Health Sciences - Summer Institute in Survey Research Techniques (September 28, 2022 11:00am) https://events.umich.edu/event/95724 95724-21790795@events.umich.edu Event Begins: Wednesday, September 28, 2022 11:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Data Collection Using Wearables, Sensors, and Apps in the Social, Behavioral, and Health Sciences

Course open for registration!
Open to all!

September 21-30, 2022
11:00am-1:00pm
Wednesdays and Fridays

The 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.

Not for academic credit.

Instructors: Florian Keusch and Heidi Guyer

All 2022 courses will be held in an alternative remote format.

]]>
Class / Instruction Wed, 22 Jun 2022 11:44:43 -0400 2022-09-28T11:00:00-04:00 2022-09-28T13:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction
Data Collection Using Wearables, Sensors, and Apps in the Social, Behavioral, and Health Sciences - Summer Institute in Survey Research Techniques (September 30, 2022 11:00am) https://events.umich.edu/event/95724 95724-21790797@events.umich.edu Event Begins: Friday, September 30, 2022 11:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Data Collection Using Wearables, Sensors, and Apps in the Social, Behavioral, and Health Sciences

Course open for registration!
Open to all!

September 21-30, 2022
11:00am-1:00pm
Wednesdays and Fridays

The 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.

Not for academic credit.

Instructors: Florian Keusch and Heidi Guyer

All 2022 courses will be held in an alternative remote format.

]]>
Class / Instruction Wed, 22 Jun 2022 11:44:43 -0400 2022-09-30T11:00:00-04:00 2022-09-30T13:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction
MGI 10th Anniversary Symposium (September 30, 2022 11:00am) https://events.umich.edu/event/97825 97825-21795204@events.umich.edu Event Begins: Friday, September 30, 2022 11:00am
Location: School of Public Health Bldg I and Crossroads and Tower
Organized By: Precision Health

At this free, in-person event, present and future users of Michigan Genomics Initiative (MGI) data can meet fellow MGI researchers and learn about the breadth and scope of ongoing MGI-supported research. We will present an overview of the available data resources to support your research, teaching, or grant writing, and explain how to access and use these resources. We will discuss our near-term and long-term goals and hope to get your input to shape our priorities.

Professor Goncalo Abecasis, D.Phil., will deliver a keynote address, and six MGI researchers will discuss their experience and highlight projects that benefited from MGI data.

Lunch will be provided, to give present and future MGI researchers, students, and postdocs the opportunity to network.

The one-day symposium will run from 11 am to 5 pm on Friday, September 30.

Attendance is free for registered participants.

Please RSVP By September 21.

]]>
Conference / Symposium Fri, 02 Sep 2022 13:03:43 -0400 2022-09-30T11:00:00-04:00 2022-09-30T17:00:00-04:00 School of Public Health Bldg I and Crossroads and Tower Precision Health Conference / Symposium Keynote Speaker Goncalo Abecasis
Code-Free Machine Learning: Introduction to Concepts and Best Practices with Hands-on Experiences - Summer Institute in Survey Research Techniques (October 5, 2022 10:00am) https://events.umich.edu/event/95713 95713-21790778@events.umich.edu Event Begins: Wednesday, October 5, 2022 10:00am
Location: Off Campus Location
Organized By: Summer Institute in Survey Research Techniques

Code-Free Machine Learning: Introduction to Concepts and Best Practices with Hands-on Experiences

Course open for registration!
Open to all!

September 7 - October 5, 2022
10:00am-12:00pm
Wednesdays

Social scientists are increasingly interested in machine learning methods to glean scientific knowledge and actionable insights from designed and gathered data. Implementing machine learning, however, requires users to have programming skills. This can be a daunting challenge for many non-tech savvy researchers. This course aims to guide social scientists to explore how machine learning can be used for their research without learning how to code. This course uses a graphical user interface tool Orange to provide learners with hands-on experiences in implementing machine learning techniques including data cleaning, visualization, and fine-tuning of algorithmic models. The open-source tool Orange is built on popular Python packages, providing basically the same functions and performances as many data scientists would obtain by writing complicated code. The course demonstrates that researchers can utilize the power of machine learning without learning how to code and focus more on machine learning concepts and best practices as well as analytical model development and validation.

Prerequisite: You must have your own laptop or desktop with Orange installed to participate in this class. For installation instruction of Orange, see https://orangedatamining.com/

Not for academic credit.

Instructor: Jinseok Kim

All 2022 courses will be held in an alternative format.

]]>
Class / Instruction Mon, 20 Jun 2022 14:53:44 -0400 2022-10-05T10:00:00-04:00 2022-10-05T12:00:00-04:00 Off Campus Location Summer Institute in Survey Research Techniques Class / Instruction
MPSDS JPSM Seminar Series - Should surveys produce more contextual features? Comparing contextual features by alternative definitions of neighborhoods (October 5, 2022 12:00pm) https://events.umich.edu/event/98386 98386-21796589@events.umich.edu Event Begins: Wednesday, October 5, 2022 12:00pm
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

MPSDS JPSM Seminar Series
October 5, 2022
12:00 - 1:00 pm

Should surveys produce more contextual features? Comparing contextual features by alternative definitions of neighborhoods.

Shiyu Zhang is a PhD candidate at the Michigan Program in Survey and Data Science. Before arriving at Michigan, she received master's degrees in immigration study, sociology and data science, and a bachelor's degree in psychology. Shiyu's dissertation focuses on the effect of adaptive survey design on estimates. She is also interested in collecting and using neighborhood features as auxiliary variables.

An important methodological challenge in studying neighborhood effects is how to geographically define “neighborhoods” and create contextual features to characterize the areas. In quantitative research that uses survey data, contextual features are commonly defined by census geographies like census tracts and block groups. However, the literature has called for expanding the definition of neighborhoods beyond census boundaries and exploring contextual features in geographic areas more relevant to the studied individuals.
In this research, we compare social and built environment features of neighborhoods based on three geographic definitions (i.e., census tracts, residential buffers, and respondent-informed neighborhoods). We evaluate how the alternatively defined measures influence the detected associations between contextual features and health outcomes. Our findings suggest that the neighborhood definition matters. Therefore, other than simply offering linkages to census boundaries based on participants’ geocoded location, surveys may enrich the data and support further research by producing and releasing case-specific contextual features.

Michigan Program in Survey and Data Science (MPSDS)
The University of Michigan Program in Survey Methodology was established in 2001 seeking to train future generations of survey and data scientists. In 2021, we changed our name to the Michigan Program in Survey and Data Science (MPSDS). Our curriculum is concerned with a broad set of data sources including survey data, but also including social media posts, sensor data, and administrative records, as well as analytic methods for working with these new data sources. And we bring to data science a focus on data quality — which is not at the center of traditional data science. The new name speaks to what we teach and work on at the intersection of social research and data. The program offers doctorate and master of science degrees and a certificate through the University of Michigan. The program's home is the Institute for Social Research, the world's largest academically-based social science research institute.

]]>
Workshop / Seminar Mon, 26 Sep 2022 11:43:15 -0400 2022-10-05T12:00:00-04:00 2022-10-05T13:00:00-04:00 Off Campus Location Michigan Program in Survey and Data Science Workshop / Seminar Flyer for Should surveys produce more contextual features? Comparing contextual features by alternative definitions of neighborhoods.
Information Session Webinar- Michigan Program in Survey and Data Science (MPSDS) (October 12, 2022 3:00pm) https://events.umich.edu/event/98336 98336-21796508@events.umich.edu Event Begins: Wednesday, October 12, 2022 3:00pm
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

Wednesday, October 12, 2002
3:00 - 4:00pm
Registration is required.

Please join us October 12, 2022 to learn about the Michigan Program in Survey and Data Science. The speaker will be Dr. Brady West.

Advance registration is required, https://bit.ly/3d3upwR

The Michigan Program in Survey and Data Science (MPSDS) offers graduate degrees that combine ideas and techniques for producing and analyzing data about humans and our society. Joint us to launch your career in this exciting and rewarding field in which scientists interpret the world through data.

The University of Michigan Program in Survey Methodology was established in 2001 seeking to train future generations of survey and data scientists. In 2021, we changed our name to the Michigan Program in Survey and Data Science. Our curriculum is concerned with a broad set of data sources including survey data, but also including social media posts, sensor data, and administrative records, as well as analytic methods for working with these new data sources. And we bring to data science a focus on data quality — which is not at the center of traditional data science. The new name speaks to what we teach and work on at the intersection of social research and data. The program offers doctorate and master of science degrees and a certificate through the University of Michigan. The program's home is the Institute for Social Research, the world's largest academically-based social science research institute.

]]>
Presentation Thu, 08 Sep 2022 14:38:06 -0400 2022-10-12T15:00:00-04:00 2022-10-12T16:00:00-04:00 Off Campus Location Michigan Program in Survey and Data Science Presentation MPSDS Informational Session Webinar
Graduate Studies in Computational & Data Sciences Information Session (October 26, 2022 1:30pm) https://events.umich.edu/event/100680 100680-21800224@events.umich.edu Event Begins: Wednesday, October 26, 2022 1:30pm
Location: Lurie Robert H. Engin. Ctr
Organized By: Michigan Institute for Computational Discovery and Engineering

The educational programs represented are:
- PhD in Scientific Computing (MICDE)
- Graduate Certificate in Computational Discovery & Engineering (MICDE)
- Graduate Certificate in Computational Neuroscience (MICDE)
- Graduate Certificate in Data Science (MIDAS)

These programs are open to all U-M graduate students with an interest in scientific computing or data science. These methodologies can have a wide range of applications - current and past students have come from a variety of home departments including Aerospace Engineering, Applied Physics, Biostatistics, Biomedical Engineering, Civil & Environmental Engineering, Chemistry, Chemical Engineering, Climate and Space Sciences and Engineering, Computational Medicine and Bioinformatics, Ecology and Evolutionary Biology, Earth and Environmental Sciences, Epidemiology, Health Behavior and Health Education, Health Infrastructures & Learning Systems, Information, Industrial & Operations Engineering, Kinesiology, Linguistics, Macromolecular Science & Engineering, Math, Molecular, Cellular, and Developmental Biology, Mechanical Engineering, Materials Science & Engineering, Naval Architecture & Marine Engineering, Nuclear Engineering & Radiological Sciences, Neuroscience, Pharmaceutical Sciences, Physics, Political Science, Psychology, Environment and Sustainability, Sociology and Statistics.

If you have any questions about these programs or about the information session, please reach out to MICDE (micde-contact@umich.edu) or MIDAS (midas-contact@umich.edu).

]]>
Presentation Tue, 25 Oct 2022 13:46:55 -0400 2022-10-26T13:30:00-04:00 2022-10-26T14:30:00-04:00 Lurie Robert H. Engin. Ctr Michigan Institute for Computational Discovery and Engineering Presentation MICDE/MIDAS Information Session - PhD in Scientific Computing (MICDE) - Graduate Certificate in Computational Discovery & Engineering (MICDE) - Graduate Certificate in Computational Neuroscience (MICDE) - Graduate Certificate in Data Science (MIDAS)
MPSDS JPSM Seminar Series - A Multivariate Stopping Rule for Survey Data Collection (November 2, 2022 12:00pm) https://events.umich.edu/event/98854 98854-21797269@events.umich.edu Event Begins: Wednesday, November 2, 2022 12:00pm
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

MPSDS JPSM Seminar Series
November 2, 2022
12:00 - 1:00 EDT

Xinyu Zhang
A Multivariate Stopping Rule for Survey Data Collection

Bio
Xinyu Zhang is a PhD candidate studying survey and data science at the University of Michigan. He is primarily interested in responsive survey designs, survey nonresponse, and machine learning techniques. His dissertation topic is using models to inform responsive survey designs.

Abstract
Surveys are experiencing declining response rates. With more and more effort expended to combat these declining response rates, the cost of large-scale surveys has continued to rise. Recent technological developments in survey data collection have allowed the survey designer to make near-real-time intervention decisions. Stopping rules are one of the interventions often considered to improve the efficiency of data collection. Stopping some cases essentially reallocates effort from stopped cases to others, but most previously proposed stopping rules have only considered single estimates. In multipurpose surveys, there may be data quality objectives that must be met for multiple estimates with constraints on costs. We introduce a stopping rule that accounts for the cost and the quality of one or more estimates. The proposed stopping rule is illustrated via simulation using data from the Health and Retirement Study.

MPSDS
The University of Michigan Program in Survey Methodology was established in 2001 seeking to train future generations of survey and data scientists. In 2021, we changed our name to the Michigan Program in Survey and Data Science. Our curriculum is concerned with a broad set of data sources including survey data, but also including social media posts, sensor data, and administrative records, as well as analytic methods for working with these new data sources. And we bring to data science a focus on data quality — which is not at the center of traditional data science. The new name speaks to what we teach and work on at the intersection of social research and data. The program offers doctorate and master of science degrees and a certificate through the University of Michigan. The program's home is the Institute for Social Research, the world's largest academically-based social science research institute.

SISRT
The mission of the Summer Institute is to provide rigorous and high quality graduate training in all phases of survey research. The 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. Graduate-level courses through the Program in Survey and Data Science are offered from June 5 through July 28 and available to enroll in as a Summer Scholar.

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.

]]>
Workshop / Seminar Tue, 01 Nov 2022 13:40:59 -0400 2022-11-02T12:00:00-04:00 2022-11-02T13:00:00-04:00 Off Campus Location Michigan Program in Survey and Data Science Workshop / Seminar Flyer
Graduate Studies in Computational & Data Sciences Information Session (November 2, 2022 1:30pm) https://events.umich.edu/event/100680 100680-21800225@events.umich.edu Event Begins: Wednesday, November 2, 2022 1:30pm
Location: West Hall
Organized By: Michigan Institute for Computational Discovery and Engineering

The educational programs represented are:
- PhD in Scientific Computing (MICDE)
- Graduate Certificate in Computational Discovery & Engineering (MICDE)
- Graduate Certificate in Computational Neuroscience (MICDE)
- Graduate Certificate in Data Science (MIDAS)

These programs are open to all U-M graduate students with an interest in scientific computing or data science. These methodologies can have a wide range of applications - current and past students have come from a variety of home departments including Aerospace Engineering, Applied Physics, Biostatistics, Biomedical Engineering, Civil & Environmental Engineering, Chemistry, Chemical Engineering, Climate and Space Sciences and Engineering, Computational Medicine and Bioinformatics, Ecology and Evolutionary Biology, Earth and Environmental Sciences, Epidemiology, Health Behavior and Health Education, Health Infrastructures & Learning Systems, Information, Industrial & Operations Engineering, Kinesiology, Linguistics, Macromolecular Science & Engineering, Math, Molecular, Cellular, and Developmental Biology, Mechanical Engineering, Materials Science & Engineering, Naval Architecture & Marine Engineering, Nuclear Engineering & Radiological Sciences, Neuroscience, Pharmaceutical Sciences, Physics, Political Science, Psychology, Environment and Sustainability, Sociology and Statistics.

If you have any questions about these programs or about the information session, please reach out to MICDE (micde-contact@umich.edu) or MIDAS (midas-contact@umich.edu).

]]>
Presentation Tue, 25 Oct 2022 13:46:55 -0400 2022-11-02T13:30:00-04:00 2022-11-02T14:30:00-04:00 West Hall Michigan Institute for Computational Discovery and Engineering Presentation MICDE/MIDAS Information Session - PhD in Scientific Computing (MICDE) - Graduate Certificate in Computational Discovery & Engineering (MICDE) - Graduate Certificate in Computational Neuroscience (MICDE) - Graduate Certificate in Data Science (MIDAS)
MPSDS JPSM Seminar Series - Accounting for Non-ignorable Sampling and Nonresponse in Statistical Matching (November 9, 2022 12:00pm) https://events.umich.edu/event/100348 100348-21799633@events.umich.edu Event Begins: Wednesday, November 9, 2022 12:00pm
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

MPSDS JPSM Seminar Series
November 9, 2022
12:00 - 1:00 EST

Accounting for Non-ignorable Sampling and Nonresponse in Statistical Matching

Danny Pfeffermann retired as the National Statistician and Director General of Israel's CBS. He is Professor Emeritus of Statistics at the Hebrew University of Jerusalem and Professor of Social Statistics at the University of Southampton. His main research areas are: Analytic inference from complex sample surveys; Seasonal adjustment and trend estimation; Small area estimation; Inference under informative sampling and nonresponse and more recently; Mode effects and Proxy surveys.

Professor Pfeffermann published about 80 articles in leading statistical journals and co-edited the two-volume handbook on Sample Surveys. He is Fellow of the American Statistical Association (ASA), the International Statistical Institute (ISI) and the Institute of Mathematical Statistics (IMS), and recipient of several international awards.

Abstract
Data for statistical analysis is often available from different samples, with each sample containing measurements on only some of the variables of interest. Statistical matching attempts to generate a fused database containing matched measurements on all the target variables. In this article, we consider the use of statistical matching when the samples are drawn by informative sampling designs and are subject to not missing at random nonresponse. The problem with ignoring the sampling process and nonresponse is that the distribution of the data observed for the responding units can be very different from the distribution holding for the population data, which may distort the inference process and result in a matched database that misrepresents the joint distribution in the population. Our proposed methodology employs the empirical likelihood approach and is shown to perform well in a simulation experiment and when applied to real sample data.

**Joint paper with Daniela Marella, to appear in International Statistical Review

MPSDS
The University of Michigan Program in Survey Methodology was established in 2001 seeking to train future generations of survey and data scientists. In 2021, we changed our name to the Michigan Program in Survey and Data Science. Our curriculum is concerned with a broad set of data sources including survey data, but also including social media posts, sensor data, and administrative records, as well as analytic methods for working with these new data sources. And we bring to data science a focus on data quality — which is not at the center of traditional data science. The new name speaks to what we teach and work on at the intersection of social research and data. The program offers doctorate and master of science degrees and a certificate through the University of Michigan. The program's home is the Institute for Social Research, the world's largest academically-based social science research institute.

SISRT
The mission of the Summer Institute is to provide rigorous and high quality graduate training in all phases of survey research. The 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. Graduate-level courses through the Program in Survey and Data Science are offered from June 5 through July 28 and available to enroll in as a Summer Scholar.

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.

]]>
Lecture / Discussion Mon, 17 Oct 2022 17:18:24 -0400 2022-11-09T12:00:00-05:00 2022-11-09T13:00:00-05:00 Off Campus Location Michigan Program in Survey and Data Science Lecture / Discussion Flyer for Accounting for Non-ignorable Sampling and Nonresponse in Statistical Matching
Information Session Webinar- Michigan Program in Survey and Data Science (MPSDS) (November 10, 2022 9:30am) https://events.umich.edu/event/100543 100543-21800056@events.umich.edu Event Begins: Thursday, November 10, 2022 9:30am
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

Thursday, November 10, 2022
9:30 - 10:30am (EST)
Registration is required, https://tinyurl.com/422xdvdp

Please join us to learn about the University of Michigan Program in Survey and Data Science.

The Michigan Program in Survey and Data Science (MPSDS) offers graduate degrees that combine ideas and techniques for producing and analyzing data about humans and our society. Join us to launch your career in this exciting and rewarding field in which scientists interpret the world through data.

MPSDS
The University of Michigan Program in Survey Methodology was established in 2001 seeking to train future generations of survey and data scientists. In 2021, we changed our name to the Michigan Program in Survey and Data Science. Our curriculum is concerned with a broad set of data sources including survey data, but also including social media posts, sensor data, and administrative records, as well as analytic methods for working with these new data sources. And we bring to data science a focus on data quality — which is not at the center of traditional data science. The new name speaks to what we teach and work on at the intersection of social research and data. The program offers doctorate and master of science degrees and a certificate through the University of Michigan. The program's home is the Institute for Social Research, the world's largest academically-based social science research institute.

]]>
Lecture / Discussion Fri, 21 Oct 2022 11:06:53 -0400 2022-11-10T09:30:00-05:00 2022-11-10T10:30:00-05:00 Off Campus Location Michigan Program in Survey and Data Science Lecture / Discussion MPSDS Informational Session Webinar
MPSDS JPSM Seminar Series - Utility of Commercial Data for Sampling Population Subgroups: A Case of Health and Retirement Study (November 16, 2022 12:00pm) https://events.umich.edu/event/101145 101145-21800872@events.umich.edu Event Begins: Wednesday, November 16, 2022 12:00pm
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

MPSDS JPSM Seminar Series
November 16, 2022
12:00 - 1:00 EST

Sunghee Lee is a Research Associate Professor at Survey Research Center, University of Michigan. Her research focuses on sampling and measurement issues with hard-to-survey population subgroups as well as racial, ethnic, and linguistic minorities.

Chendi Zhao is a Research Assistant and first-year Ph.D. student in the Program in Survey and Data Science

Anqi Liu is a master’s student in MPSDS at the University of Michigan. She works closely with Dr. Sunghee Lee on the Health and Retirement Study sampling.

Abstract
A standard approach for targeting population subgroups in household surveys is to sample general population and then to screen for eligible households. This becomes increasingly costly as the subgroup accounts for a small proportion of the population, which is the case for the Health and Retirement Study (HRS). HRS is a population-based longitudinal study of adults ages 50 and older in the U.S. and maintains its representativeness by adding a new age cohort every 6 years. In 2016, HRS targeted those born between 1960 and 1965 with an additional goal of oversampling racial/ethnic minorities. This group is less than 10% of the population. In order to increase the efficiency of screening, HRS had traditionally used probability proportionate size sampling in its area-probability sample with the age-eligible population size as a measure of size as well as stratification based on the race/ethnicity distribution of area sampling units. For 2016, HRS sampling additionally used stratification at the address level by enhancing the population of addresses in the sample areas with commercial data. This study examines the utility of commercial data for increasing efficiency with a focus on its availability and accuracy by analyzing a dataset that combines sampling frame data, screening data, main survey data as well as external data from the American Community Survey.

MPSDS
The University of Michigan Program in Survey Methodology was established in 2001 seeking to train future generations of survey and data scientists. In 2021, we changed our name to the Michigan Program in Survey and Data Science. Our curriculum is concerned with a broad set of data sources including survey data, but also including social media posts, sensor data, and administrative records, as well as analytic methods for working with these new data sources. And we bring to data science a focus on data quality — which is not at the center of traditional data science. The new name speaks to what we teach and work on at the intersection of social research and data. The program offers doctorate and master of science degrees and a certificate through the University of Michigan. The program's home is the Institute for Social Research, the world's largest academically-based social science research institute.

SISRT
The Annual Summer Institute in Survey Research Techniques
The mission of the Summer Institute is to provide rigorous and high quality graduate training in all phases of survey research. The 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. Graduate-level courses through the Program in Survey and Data Science are offered from June 5 through July 28 and available to enroll in as a Summer Scholar.

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.

]]>
Lecture / Discussion Mon, 07 Nov 2022 18:46:54 -0500 2022-11-16T12:00:00-05:00 2022-11-16T13:00:00-05:00 Off Campus Location Michigan Program in Survey and Data Science Lecture / Discussion Flyer
Sharing Data with the National Addiction & HIV Data Archive Program (NAHDAP): Meeting the Requirements of the New NIH Data Sharing Policy (December 5, 2022 1:00pm) https://events.umich.edu/event/101349 101349-21801251@events.umich.edu Event Begins: Monday, December 5, 2022 1:00pm
Location: Off Campus Location
Organized By: Institute for Social Research

The National Addiction & HIV Data Archive Program (NAHDAP) is a data archive at ICPSR, the University of Michigan, which facilitates research on drug addiction and HIV infection by acquiring, enhancing, preserving, and sharing data produced by research grants, particularly those funded by the National Institute on Drug Abuse (NIDA). NAHDAP staff work with researchers to safely share their data, including sensitive data, for long-term preservation and secure access by the research community. NAHDAP provides services to help grantees meet the data sharing requirements for their current NIH grants, and to help future grantees plan to meet data sharing requirements for upcoming grants, particularly in light of the new NIH Data Management and Sharing Policy.

In this webinar, you will learn:
● What services NAHDAP provides and what types of data are a good fit for NAHDAP
● Why you should consider sharing your data with NAHDAP
● How NAHDAP protects sensitive or restricted data
● How you can use NAHDAP to meet the data sharing requirements of your NIH grant
● How to write an NIH Data Management and Sharing Plan as a social or behavioral scientist using NAHDAP

Who should attend?
This webinar is free and open to the public. It will be most useful for current or prospective NIH grantees, with a research focus on drug use, addiction, and/or HIV topics, who expect to share data in the future.

Register here: https://myumi.ch/9P24g

]]>
Presentation Mon, 14 Nov 2022 16:21:34 -0500 2022-12-05T13:00:00-05:00 2022-12-05T14:00:00-05:00 Off Campus Location Institute for Social Research Presentation This image includes the title, date/time, and registration link of the webinar. It also includes a stock image of two people smiling.
MPSDS JPSM Seminar Series - The Role of Data Collection in Population Science: Contemporary Studies from ABCD to HBCD (January 20, 2023 2:00pm) https://events.umich.edu/event/103756 103756-21807773@events.umich.edu Event Begins: Friday, January 20, 2023 2:00pm
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

MPSDS JPSM Seminar Series
February 1, 2023
12:00 - 1:00 EST

The Role of Data Collection in Population Science: Contemporary Studies from ABCD to HBCD

Abstract

Recently nationwide consortiums of multiple research sites have conducted multi-modal, longitudinal cohort studies and provided unprecedented data sources for population science research. For example, the Adolescent Brain Cognitive Development (ABCD) Study has collected data from 11,880 children ages 9-10 across 21 U.S. research sites, as the largest long-term study of brain development and child health; and the Healthy Brain and Child Development (HBCD) Study will enroll 7,500 pregnant women across 25 research sites and follow them from pregnancy through early childhood, as the largest long-term study of early brain and child development in the U.S. Both studies aim to reflect the sociodemographic diversity of the target population to enable characterization of natural variability and trajectories. Without probability sampling as the touchstone for randomization-based inferences, the data quality and analysis validity require rigorous evaluations and potentially rely on untestable assumptions. The data collection process also presents various challenges during practical operation.

In this talk, I look into both inference and design schemes to study the impact of data collection on population science. First, using the ABCD study as an example of secondary data analysis, I discuss inference approaches focusing on multilevel regression and poststratification for population generalizability and latent subgroup detection for population heterogeneity in brain activity and association studies. Second, I introduce the HBCD study design. HBCD also aims to include individuals demographically and behaviorally similar to those in the substance exposure group, but without exposure, to enable valid causal inference in a non-experimental study design. I discuss our proposed weighting, matching, and modeling strategies to leverage analysis goals to inform the design and dashboard monitoring for adaptive sample enrollment.

Bio

Yajuan Si is a Research Associate Professor in the Institute for Social Research at the University of Michigan. Dr Si’s research lies in cutting-edge methodology development in streams of Bayesian statistics, linking design- and model-based approaches for survey inference, missing data analysis, confidentiality protection involving the creation and analysis of synthetic datasets, and causal inference with observational data.

Michigan Program in Survey and Data Science (MPSDS)
The University of Michigan Program in Survey Methodology was established in 2001 seeking to train future generations of survey and data scientists. In 2021, we changed our name to the Michigan Program in Survey and Data Science. Our curriculum is concerned with a broad set of data sources including survey data, but also including social media posts, sensor data, and administrative records, as well as analytic methods for working with these new data sources. And we bring to data science a focus on data quality — which is not at the center of traditional data science. The new name speaks to what we teach and work on at the intersection of social research and data. The program offers doctorate and master of science degrees and a certificate through the University of Michigan. The program's home is the Institute for Social Research, the world's largest academically-based social science research institute.

Summer Institute in Survey Research Techniques (SISRT)
The mission of the Summer Institute is to provide rigorous and high quality graduate training in all phases of survey research. The 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. Graduate-level courses through the Program in Survey and Data Science are offered from June 5 through July 28 and available to enroll in as a Summer Scholar.

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.

]]>
Lecture / Discussion Fri, 20 Jan 2023 14:51:50 -0500 2023-01-20T14:00:00-05:00 2023-01-20T15:00:00-05:00 Off Campus Location Michigan Program in Survey and Data Science Lecture / Discussion Flyer
MPSDS JPSM Seminar Series - The Role of Data Collection in Population Science: Contemporary Studies from ABCD to HBCD (January 20, 2023 2:00pm) https://events.umich.edu/event/103756 103756-21807774@events.umich.edu Event Begins: Friday, January 20, 2023 2:00pm
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

MPSDS JPSM Seminar Series
February 1, 2023
12:00 - 1:00 EST

The Role of Data Collection in Population Science: Contemporary Studies from ABCD to HBCD

Abstract

Recently nationwide consortiums of multiple research sites have conducted multi-modal, longitudinal cohort studies and provided unprecedented data sources for population science research. For example, the Adolescent Brain Cognitive Development (ABCD) Study has collected data from 11,880 children ages 9-10 across 21 U.S. research sites, as the largest long-term study of brain development and child health; and the Healthy Brain and Child Development (HBCD) Study will enroll 7,500 pregnant women across 25 research sites and follow them from pregnancy through early childhood, as the largest long-term study of early brain and child development in the U.S. Both studies aim to reflect the sociodemographic diversity of the target population to enable characterization of natural variability and trajectories. Without probability sampling as the touchstone for randomization-based inferences, the data quality and analysis validity require rigorous evaluations and potentially rely on untestable assumptions. The data collection process also presents various challenges during practical operation.

In this talk, I look into both inference and design schemes to study the impact of data collection on population science. First, using the ABCD study as an example of secondary data analysis, I discuss inference approaches focusing on multilevel regression and poststratification for population generalizability and latent subgroup detection for population heterogeneity in brain activity and association studies. Second, I introduce the HBCD study design. HBCD also aims to include individuals demographically and behaviorally similar to those in the substance exposure group, but without exposure, to enable valid causal inference in a non-experimental study design. I discuss our proposed weighting, matching, and modeling strategies to leverage analysis goals to inform the design and dashboard monitoring for adaptive sample enrollment.

Bio

Yajuan Si is a Research Associate Professor in the Institute for Social Research at the University of Michigan. Dr Si’s research lies in cutting-edge methodology development in streams of Bayesian statistics, linking design- and model-based approaches for survey inference, missing data analysis, confidentiality protection involving the creation and analysis of synthetic datasets, and causal inference with observational data.

Michigan Program in Survey and Data Science (MPSDS)
The University of Michigan Program in Survey Methodology was established in 2001 seeking to train future generations of survey and data scientists. In 2021, we changed our name to the Michigan Program in Survey and Data Science. Our curriculum is concerned with a broad set of data sources including survey data, but also including social media posts, sensor data, and administrative records, as well as analytic methods for working with these new data sources. And we bring to data science a focus on data quality — which is not at the center of traditional data science. The new name speaks to what we teach and work on at the intersection of social research and data. The program offers doctorate and master of science degrees and a certificate through the University of Michigan. The program's home is the Institute for Social Research, the world's largest academically-based social science research institute.

Summer Institute in Survey Research Techniques (SISRT)
The mission of the Summer Institute is to provide rigorous and high quality graduate training in all phases of survey research. The 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. Graduate-level courses through the Program in Survey and Data Science are offered from June 5 through July 28 and available to enroll in as a Summer Scholar.

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.

]]>
Lecture / Discussion Fri, 20 Jan 2023 14:51:50 -0500 2023-01-20T14:00:00-05:00 2023-01-20T15:00:00-05:00 Off Campus Location Michigan Program in Survey and Data Science Lecture / Discussion Flyer
Ahead of the Curve featuring Dr. Sanjay Gupta (February 1, 2023 4:00pm) https://events.umich.edu/event/103680 103680-21807637@events.umich.edu Event Begins: Wednesday, February 1, 2023 4:00pm
Location: Off Campus Location
Organized By: School of Public Health

Dr. Sanjay Gupta has become synonymous with health communications over the past two decades in his roles as CNN's Chief Medical Correspondent, podcast host, and author. The two-time University of Michigan graduate ('90, MD '93) continues to work as a practicing neurosurgeon in Atlanta as well. Gupta will join Dean DuBois Bowman for a conversation on leadership, communication, and trust during this edition of the "Ahead of the Curve" speaker series. The event will be streamed, and is free and open to the public. Please register to receive the streaming link.

]]>
Livestream / Virtual Tue, 31 Jan 2023 11:34:25 -0500 2023-02-01T16:00:00-05:00 2023-02-01T17:00:00-05:00 Off Campus Location School of Public Health Livestream / Virtual Dr. Sanjay Gupta
MPSDS JPSM Seminar Series - The Evolution of the Use of Models in Survey Sampling (February 15, 2023 12:00pm) https://events.umich.edu/event/103587 103587-21807518@events.umich.edu Event Begins: Wednesday, February 15, 2023 12:00pm
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

MPSDS JPSM Seminar Series
February 15, 2023
12:00 - 1:00 EST

Richard Valliant, PhD, is a research professor emeritus at the Institute for Social Research, University of Michigan, and at the Joint Program in Survey Methodology at the University of Maryland. He is a Fellow of the American Statistical Association, an elected member of the International Statistical Institute, and has been an associate editor of the Journal of the American Statistical Association, Journal of Official Statistics, and Survey Methodology.

The Evolution of the Use of Models in Survey Sampling

The use of models in survey estimation has evolved over the last five (or more) decades. This talk will trace some of the developments over time and attempt to review some of the history. Consideration of models for estimating descriptive statistics began as early as the 1940's when Cochran and Jessen proposed linear regression estimators of means. These were early examples of model-assisted estimation since the properties of the Cochran-Jessen estimators were calculated with respect to a random sampling distribution. Model-thinking was used informally through the 1960's to form ratio and linear regression estimators that could in some applications reduce design variances.

In a 1963 Australian Journal of Statistics paper, Brewer presented results for a ratio estimator that were entirely based on a super population model. Royall (Biometrika 1970 and later papers) formalized the theory for a more general prediction approach using linear models. Since that time, the use of models is ubiquitous in the survey estimation literature and has been extended to nonparametric, empirical likelihood, Bayesian, small area, machine learning, and other approaches. There remains a considerable gap between the more advanced techniques in the literature and the methods commonly used in practice.

In parallel to the model developments, the design-based, randomization approach was dominating official statistics in the US largely due to the efforts of Morris Hansen and his colleagues at the US Census Bureau. In 1937 Hansen and others at the Census Bureau designed a follow-on sample survey to a special census of the employed and partially employed because response to the census was incomplete and felt to be inaccurate. The sample estimates were judged to be more trustworthy than those of the census itself. This began Hansen’s career-long devotion to random sampling as the only trustworthy method for obtaining samples from finite populations and for making inferences.

Model-assisted estimation, as discussed in the 1992 book by Särndal, Swensson, and Wretman is a type of compromise where models are used to construct estimators while a randomization distribution is used to compute properties like means and variances. This thinking has led to the popularity of doubly robust approaches where the goal is to have estimators with good properties with respect to both a randomization and a model distribution.

The field has now reached a troubling crossroads in which response rates to many types of surveys have plummeted and nonprobability datasets are touted as a way of obtaining reasonable quality data at low cost. Sophisticated model-based mathematical methods have been developed for estimation from nonprobability samples. In some applications, e.g., administrative data files that are incomplete due to late reporting, these methods may work well. However, in others the quality of nonprobability sample data is irremediably bad as illustrated by Kennedy in her 2022 Hansen lecture. In some situations, we are back in Morris' 1937 situation where standard approaches no longer work. Methods are needed to evaluate whether acceptable estimates can be made from the most suspect data sets. Nonetheless. nonprobability datasets are readily available now, and it is up to the statistical profession to develop good methods for using them.

Michigan Program in Survey and Data Science (MPSDS)
The University of Michigan Program in Survey Methodology was established in 2001 seeking to train future generations of survey and data scientists. In 2021, we changed our name to the Michigan Program in Survey and Data Science. Our curriculum is concerned with a broad set of data sources including survey data, but also including social media posts, sensor data, and administrative records, as well as analytic methods for working with these new data sources. And we bring to data science a focus on data quality — which is not at the center of traditional data science. The new name speaks to what we teach and work on at the intersection of social research and data. The program offers doctorate and master of science degrees and a certificate through the University of Michigan. The program's home is the Institute for Social Research, the world's largest academically-based social science research institute.

Summer Institute in Survey Research Techniques (SISRT)
The mission of the Summer Institute is to provide rigorous and high quality graduate training in all phases of survey research. The 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. Graduate-level courses through the Program in Survey and Data Science are offered from June 5 through July 28 and available to enroll in as a Summer Scholar.

]]>
Lecture / Discussion Wed, 18 Jan 2023 15:55:19 -0500 2023-02-15T12:00:00-05:00 2023-02-15T13:00:00-05:00 Off Campus Location Michigan Program in Survey and Data Science Lecture / Discussion Flyer
MPSDS JPSM Seminar Series - Network Size: Measurement and Errors (March 8, 2023 12:00pm) https://events.umich.edu/event/104021 104021-21808283@events.umich.edu Event Begins: Wednesday, March 8, 2023 12:00pm
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

MPSDS JPSM Seminar Series
March 8, 2023
12:00 - 1:00 EST

Abstract
Respondent driven sampling (RDS) is a sampling method that leverages the respondents' networks to reach more members of the target population. In RDS, the size of the respondents' social network (also known as personal network size (PNS), or respondent's degree) is important in both the study operations and in estimation. A commonly used estimation of degree is the self-reported data from the interview, which typically has substantial measurement error, and, specifically, is found to be frequently rounded to a multiple of five. Measurement error in the PNS can introduce biased estimates for RDS, especially if the misreporting of the degree is associated with the outcome to be estimated.

This brown bag will present two related studies on the measurement of PNS. The first study uses two sets of data; 1) semi-structured in-depth interviews conducted over Zoom with 19 adult respondents of various ages, gender identities (transgender, nonbinary, cisgender), race, and sexual orientations (gay, lesbian, bi), 2) an RDS web survey targeting the adult LGBT population (n = 394). Thematic analysis conducted on the semi-structured interview transcripts showed a large variation in how respondents define "knowing" someone; for some respondents, it covers a larger network than the "recruitable" network (the network of people respondents are likely to think of recruiting to an RDS study). Meanwhile, the web-RDS shows that the more restrictive PNS questions yielded more realistic ranges for a "recruitable" network, with less proportion of rounded responses on the more restrictive PNS questions.

Motivated by the desire to improve the degree estimation in RDS, the second study presents a latent variable model to make inferences about participants’ actual degrees and potential reporting behaviors. Specifically, individual-level degree estimation will be obtained by revealing the association between the actual degree and relevant personal characteristics and blending their response to “How many [a particular sub-population] do you know in the target population?” Simulation studies demonstrate that the proposed method delivers sensible estimations about the individual degree.

Bios
Ai Rene Ong works at American Institutes for Research (AIR) as a Researcher/Survey Methodologist in the area of Education Statistics. She graduated with a PhD in Survey Methodology from the University of Michigan in 2022. Her dissertation research was on the measurement of network size and the mechanism of peer recruitment in Respondent Driven Sampling — a sampling method typically used for hard-to-sample populations.

Yibo Wang is a 3rd year Ph.D. candidate from the department of Biostatistics. She is now working with Dr. Sunghee Lee and Dr. Michael Elliott on measurement estimation in Respondent Driven Sampling

Michigan Program in Survey and Data Science (MPSDS)
The University of Michigan Program in Survey Methodology was established in 2001 seeking to train future generations of survey and data scientists. In 2021, we changed our name to the Michigan Program in Survey and Data Science. Our curriculum is concerned with a broad set of data sources including survey data, but also including social media posts, sensor data, and administrative records, as well as analytic methods for working with these new data sources. And we bring to data science a focus on data quality — which is not at the center of traditional data science. The new name speaks to what we teach and work on at the intersection of social research and data. The program offers doctorate and master of science degrees and a certificate through the University of Michigan. The program's home is the Institute for Social Research, the world's largest academically-based social science research institute.

Summer Institute in Survey Research Techniques (SISRT)
The mission of the Summer Institute is to provide rigorous and high quality graduate training in all phases of survey research. The 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. Graduate-level courses through the Program in Survey and Data Science are offered from June 5 through July 28 and available to enroll in as a Summer Scholar.

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.

]]>
Lecture / Discussion Wed, 25 Jan 2023 14:08:47 -0500 2023-03-08T12:00:00-05:00 2023-03-08T13:00:00-05:00 Off Campus Location Michigan Program in Survey and Data Science Lecture / Discussion Flyer
MPSDS JPSM Seminar Series - How to ask for consent to data linkage: Things we’ve learnt (March 15, 2023 12:00pm) https://events.umich.edu/event/104312 104312-21808815@events.umich.edu Event Begins: Wednesday, March 15, 2023 12:00pm
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

MPSDS JPSM Seminar Series
March 15, 2023
12:00 - 1:00 EST

The Zoom call will be locked 10 minutes after the start of the presentation.

Annette Jäckle is Professor of Survey Methodology at the Institute for Social and Economic Research at the University of Essex, UK and Associate Director of Innovations and Co-Investigator of the UK Household Longitudinal Study: Understanding Society. Her research interests are in methodology of data collection for longitudinal studies, mixed mode data collection, questionnaire design, respondent consent to data linkage, and new ways of using mobile devices for survey data collection.

Abstract
Data linkage usually requires informed consent of respondents, whether for legal or ethical reasons. A common problem is that when consent questions are asked in self-completion surveys, respondents are much less likely to consent than when they are asked for consent in interviewer administered surveys. In the existing literature, predictors of consent are mostly inconsistent, between studies, but also between different consents asked within one study. In addition, experiments with the wording of consent questions have often had no or inconsistent effects. Why is this? And what can be done to increase informed consent to data linkage? This presentation provides an overview of what we have learnt from qualitative in-depth interviews and a series of experiments implemented in two UK probability household panels (the Understanding Society Innovation Panel and COVID-19 study) and in the UK PopulusLive online access panel. We address the following questions. (1) How do respondents decide whether to consent to data linkage? (2) Why are respondents less likely to consent in web than CAPI surveys? (3) How best to ask for multiple consents within a survey? (4) Which wording and formats affect informed consent and why? We end the overview with a summary of the practical implications for how best to ask for consent to data linkage.

Michigan Program in Survey and Data Science (MPSDS)
The University of Michigan Program in Survey Methodology was established in 2001 seeking to train future generations of survey and data scientists. In 2021, we changed our name to the Michigan Program in Survey and Data Science. Our curriculum is concerned with a broad set of data sources including survey data, but also including social media posts, sensor data, and administrative records, as well as analytic methods for working with these new data sources. And we bring to data science a focus on data quality — which is not at the center of traditional data science. The new name speaks to what we teach and work on at the intersection of social research and data. The program offers doctorate and master of science degrees and a certificate through the University of Michigan. The program's home is the Institute for Social Research, the world's largest academically-based social science research institute.

Summer Institute in Survey Research Techniques (SISRT)
The mission of the Summer Institute is to provide rigorous and high quality graduate training in all phases of survey research. The 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. Graduate-level courses through the Program in Survey and Data Science are offered from June 5 through July 28 and available to enroll in as a Summer Scholar.

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.

]]>
Lecture / Discussion Wed, 15 Mar 2023 08:14:34 -0400 2023-03-15T12:00:00-04:00 2023-03-15T13:00:00-04:00 Off Campus Location Michigan Program in Survey and Data Science Lecture / Discussion Flyer
Virtual Webinar: The US COVID-19 County Policy Database: a novel resource to support pandemic-related research (March 23, 2023 3:00pm) https://events.umich.edu/event/105335 105335-21811573@events.umich.edu Event Begins: Thursday, March 23, 2023 3:00pm
Location:
Organized By: Inter-university Consortium for Political and Social Research

It is increasingly recognized that policies have played a role in both alleviating and exacerbating the health and economic consequences of the COVID-19 pandemic. While prior work has focused on characterizing and analyzing the effects of federal and state policies, there has been limited systematic evaluation of variation in U.S. local (i.e., county) COVID-19-related policies. This virtual webinar introduces the U.S. COVID-19 County Policy (UCCP) Database, whose objective is to systematically gather, characterize, and assess variation in U.S. county-level COVID-19-related policies. Data collection is still ongoing for this NIH and PCORI-funded database. Dr. Hamad will describe the data collection methods and some preliminary results. Register for this virtual webinar here: https://myumi.ch/NkmZk

]]>
Workshop / Seminar Wed, 22 Feb 2023 16:21:25 -0500 2023-03-23T15:00:00-04:00 2023-03-23T16:00:00-04:00 Inter-university Consortium for Political and Social Research Workshop / Seminar A campaign photo that includes information about the Webinar
MPSDS JPSM Seminar Series - Assessing Cross-Cultural Comparability of Self-Rated Health and Its Conceptualization through Web Probing (April 5, 2023 12:00pm) https://events.umich.edu/event/103497 103497-21807352@events.umich.edu Event Begins: Wednesday, April 5, 2023 12:00pm
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

MPSDS JPSM Seminar Series
April 5, 2022
12:00 - 1:00 EST

Stephanie Morales is a second-year Ph.D. student at the University of Michigan's Program in Survey and Data Science. She holds a BA in Psychology and an MA in Sociology. She is interested in cross-cultural surveys, measurement error in data collection with racial/ethnic minorities, and adaptive survey design.

Assessing Cross-Cultural Comparability of Self-Rated Health and Its Conceptualization through Web Probing

Self-rated health (SRH) is a widely used question across different fields, as it is simple to administer yet has been shown to predict mortality. SRH asks respondents to rate their overall health typically using Likert-type response scales (i.e., excellent, very good, good, fair, poor). Although SRH is commonly used, few studies have examined its conceptualization from the respondents’ point of view and even less so for differences in its conceptualization across diverse populations. We aim to assess the comparability of SRH across different cultural groups by investigating the factors that respondents consider when responding to the SRH question. We included an open-ended probe asking what respondents thought when responding to SRH in web surveys conducted in five countries: Great Britain, Germany, the U.S., Spain, and Mexico. In the U.S., we targeted six racial/ethnic and linguistic groups: English-dominant Koreans, Korean-dominant Koreans, English-dominant Latinos, Spanish-dominant Latinos, non-Latino Black Americans, and non-Latino White Americans. One novelty of our study is allowing multiple attribute codes (e.g., health behaviors, illness) per respondent and tone (e.g., in the direction of positive or negative health or neutral) of the probing responses for each attribute, allowing us 1) to assess respondents’ thinking process holistically and 2) to examine whether and how respondents mix attributes. Our study compares the number of reported attributes and tone by cultural groups and integrates SRH responses in the analysis. This study aims to provide a deeper understanding of SRH by revealing the cognitive processes among diverse populations and is expected to shed light on its cross-cultural comparability.

Michigan Program in Survey and Data Science (MPSDS)
The University of Michigan Program in Survey Methodology was established in 2001 seeking to train future generations of survey and data scientists. In 2021, we changed our name to the Michigan Program in Survey and Data Science. Our curriculum is concerned with a broad set of data sources including survey data, but also including social media posts, sensor data, and administrative records, as well as analytic methods for working with these new data sources. And we bring to data science a focus on data quality — which is not at the center of traditional data science. The new name speaks to what we teach and work on at the intersection of social research and data. The program offers doctorate and master of science degrees and a certificate through the University of Michigan. The program's home is the Institute for Social Research, the world's largest academically-based social science research institute.

Summer Institute in Survey Research Techniques (SISRT)
The mission of the Summer Institute is to provide rigorous and high quality graduate training in all phases of survey research. The 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. Graduate-level courses through the Program in Survey and Data Science are offered from June 5 through July 28 and available to enroll in as a Summer Scholar.

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.

]]>
Lecture / Discussion Mon, 16 Jan 2023 17:00:12 -0500 2023-04-05T12:00:00-04:00 2023-04-05T13:00:00-04:00 Off Campus Location Michigan Program in Survey and Data Science Lecture / Discussion Flyer
Analyzing Data on Arts and Culture in Large-scale Health, Education, and Labor Studies (April 18, 2023 1:00pm) https://events.umich.edu/event/106098 106098-21813746@events.umich.edu Event Begins: Tuesday, April 18, 2023 1:00pm
Location: Off Campus Location
Organized By: Inter-university Consortium for Political and Social Research

This webinar, hosted by the National Archive of Data on Arts & Culture (NADAC) and moderated by Melissa Menzer, a Senior Program Analyst in the Office of Research & Analysis at the NEA, will introduce participants to NEA research priority areas, their research grant funding opportunities, and several examples of research projects funded by the NEA research awards that use datasets archived or cataloged in NADAC. Presentations from the webinar panelists will cover the Health and Retirement Study, various datasets from the National Center of Education Statistics, and the Strategic National Arts Alumni Project (SNAAP). Panelists will share their successes and challenges working with these datasets and/or working with data repositories to analyze data. Panelists include Jennifer Novak-Leonard (University of Illinois at Urbana-Champaign), Kenneth Elpus (University of Maryland School of Music), and Hei Wan (Karen) Mak (World Health Organization Collaborating Centre on Arts and Health). This webinar is free and open to the public. To register, go to https://myumi.ch/1A6pb.

]]>
Presentation Sun, 12 Mar 2023 23:18:32 -0400 2023-04-18T13:00:00-04:00 2023-04-18T14:30:00-04:00 Off Campus Location Inter-university Consortium for Political and Social Research Presentation Webinar: Analyzing Data on Arts and Culture in Large-scale Health, Education, and Labor Studies