Happening @ Michigan https://events.umich.edu/list/rss RSS Feed for Happening @ Michigan Events at the University of Michigan. CoderSpaces: Tuesdays Winter 2023 (February 7, 2023 9:30am) https://events.umich.edu/event/103187 103187-21806262@events.umich.edu Event Begins: Tuesday, February 7, 2023 9:30am
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:15:11 -0500 2023-02-07T09:30:00-05:00 2023-02-07T11:00:00-05:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces Winter 2023 - weekly data science hubs via Zoom
Privacy@Michigan: Child Safety in the Smart Home (February 8, 2023 12:00pm) https://events.umich.edu/event/104342 104342-21808844@events.umich.edu Event Begins: Wednesday, February 8, 2023 12:00pm
Location: Off Campus Location
Organized By: Information and Technology Services (ITS)

The adoption of home devices connected to the internet is growing and so are concerns about child physical and digital safety and privacy in the smart home. The U-M community is invited to join us on Zoom for a presentation and Q&A with Kaiwen Sun, U-M School of Information Ph.D. student, as she explores the discrepancies between marketing depictions and device features, and discusses considerations for keeping children safe in the smart home.

Kaiwen Sun’s research focuses on the intersection of children’s privacy and safety and understanding parents’ perceptions and behaviors around privacy and safety in the context of smart home technologies.

This event is open to the U-M community (umich login required) and will be especially relevant to parents, grandparents, guardians, and others who interact with children in their homes.

Zoom link: https://umich.zoom.us/j/99704278354?pwd=ejJzL2NDNDhPVHkwM3pobHUxVXREdz09

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Livestream / Virtual Wed, 08 Feb 2023 10:08:51 -0500 2023-02-08T12:00:00-05:00 2023-02-08T13:00:00-05:00 Off Campus Location Information and Technology Services (ITS) Livestream / Virtual Privacy at Michigan - Child Safety in the Smart Home Presentation and Q and A
CoderSpaces: Wednesdays Winter 2023 (February 8, 2023 1:30pm) https://events.umich.edu/event/103188 103188-21806278@events.umich.edu Event Begins: Wednesday, February 8, 2023 1:30pm
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:18:31 -0500 2023-02-08T13:30:00-05:00 2023-02-08T15:00:00-05:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces - weekly data science hubs via Zoom
CoderSpaces: Tuesdays Winter 2023 (February 14, 2023 9:30am) https://events.umich.edu/event/103187 103187-21806263@events.umich.edu Event Begins: Tuesday, February 14, 2023 9:30am
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:15:11 -0500 2023-02-14T09:30:00-05:00 2023-02-14T11:00:00-05:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces Winter 2023 - weekly data science hubs via Zoom
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.

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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
CoderSpaces: Wednesdays Winter 2023 (February 15, 2023 1:30pm) https://events.umich.edu/event/103188 103188-21806279@events.umich.edu Event Begins: Wednesday, February 15, 2023 1:30pm
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:18:31 -0500 2023-02-15T13:30:00-05:00 2023-02-15T15:00:00-05:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces - weekly data science hubs via Zoom
CoderSpaces: Tuesdays Winter 2023 (February 21, 2023 9:30am) https://events.umich.edu/event/103187 103187-21806264@events.umich.edu Event Begins: Tuesday, February 21, 2023 9:30am
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:15:11 -0500 2023-02-21T09:30:00-05:00 2023-02-21T11:00:00-05:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces Winter 2023 - weekly data science hubs via Zoom
LHS Collaboratory Joint Session with UM School of Dentistry (February 21, 2023 12:00pm) https://events.umich.edu/event/102701 102701-21805007@events.umich.edu Event Begins: Tuesday, February 21, 2023 12:00pm
Location: Off Campus Location
Organized By: Department of Learning Health Sciences

“The Future is Data Analytics: Many Challenges, Many Opportunities”

Keynote Speaker:

Lawrence A. Tabak, DDS, PhD
Director
National Institutes of Health (NIH)

Register in advance via Zoom Webinar: https://umich.zoom.us/webinar/register/WN_GyKMMpgVQHu2ezvxaJfZEA#/registration

12:00 pm-1:15 pm ET (Keynote)

1:30 pm-2:15 pm ET (Breakout rooms)

The keynote presentation (12:00 pm-1:15 pm ET) will be followed by breakout rooms (1:30 pm-2:15 pm ET) on topics presented by the UM faculty and guests.

Opening Remarks:
Laurey McCauley, DDS, MS, PHD

Breakout room #1: Data Integration and Sharing: Opportunities in Entrepreneurship and Research

Wenyuan Shi, PhD
Presentation: Building the Eco-system to Support Disruptive Technologies in Dentistry

Christopher Balaban, DMD, MSC, FACD
Presentation: Entrepreneurship and AI/LHS in Dentistry

Breakout room # 2 Data Integration and Sharing in/out of the Clinic: New Medical and Dental technologies and LHS methods to optimize care

Alexandre F. M. DaSilva, DDS, DMedSc
Presentation: Integrating and Sharing Dental and Medical Data in a Diverse Ecosystem – The Learning Health Systems Perspective

Muhammad F. Walji, PhD
Presentation: BigMouth: Lessons Learned from a Decade of Sharing EHR Data in Dentistry

Breakout room #3: Data Integration and Sharing in Imaging and Pharmacogenetics

Lucia Cevidanes, DDS, MS, PhD
Presentation: Innovations in Multimodal Imaging Data Integration and Sharing

Amy Pasternak, PharmD
Presentation: Integrating Pharmacogenomics into Daily Practice

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Livestream / Virtual Thu, 26 Jan 2023 23:22:37 -0500 2023-02-21T12:00:00-05:00 2023-02-21T14:00:00-05:00 Off Campus Location Department of Learning Health Sciences Livestream / Virtual LHS Collaboratory logo
CoderSpaces: Wednesdays Winter 2023 (February 22, 2023 1:30pm) https://events.umich.edu/event/103188 103188-21806280@events.umich.edu Event Begins: Wednesday, February 22, 2023 1:30pm
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:18:31 -0500 2023-02-22T13:30:00-05:00 2023-02-22T15:00:00-05:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces - weekly data science hubs via Zoom
Key Takeaways from ASTHO’s 2019 Profile Survey on State and Territorial Public Health (February 23, 2023 1:00pm) https://events.umich.edu/event/104682 104682-21809826@events.umich.edu Event Begins: Thursday, February 23, 2023 1:00pm
Location: Off Campus Location
Organized By: Inter-university Consortium for Political and Social Research

The Health and Medical Care Archive (HMCA), the dedicated archive of the Robert Wood Johnson Foundation (RWJF), will host a free webinar Thursday, Feb. 23rd at 1:00 EST about The Association of State and Territorial Health Officials' (ASTHO) 2019 data.

ASTHO will provide an overview of the ASTHO Profile Survey of State and Territorial Public Health, the only comprehensive source of information on state public health resources, governance, and infrastructure. This survey is fielded every three years to all state health agencies, including D.C., and 8 island jurisdictions. This presentation will focus on key findings from 2019 data and how it was used to understand the context around state public health infrastructure prior to the COVID-19 pandemic.

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Presentation Wed, 08 Feb 2023 16:24:56 -0500 2023-02-23T13:00:00-05:00 2023-02-23T17:00:00-05:00 Off Campus Location Inter-university Consortium for Political and Social Research Presentation Promotional image for Key Takeaways from ASTHO’s 2019 Profile Survey on State and Territorial Public Health webinar
MIDAS Data and AI in Society Forum: Artificial Intelligence in the Classroom (February 24, 2023 1:30pm) https://events.umich.edu/event/104347 104347-21808848@events.umich.edu Event Begins: Friday, February 24, 2023 1:30pm
Location: Weiser Hall
Organized By: Michigan Institute for Data Science

If the headlines are to be believed, higher education is about to face its biggest disruption in history. But will artificial intelligence tools really “end higher education as we know it,” “revolutionize the classroom,” or something else?
Join us to explore the role of AI in the classroom at this exciting panel event.

Cosponsored by LSA and the Michigan AI Laboratory.

Read more and register to attend on the event webpage: https://midas.umich.edu/classroom-ai-forum/

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Lecture / Discussion Fri, 03 Feb 2023 15:28:56 -0500 2023-02-24T13:30:00-05:00 2023-02-24T15:00:00-05:00 Weiser Hall Michigan Institute for Data Science Lecture / Discussion AI-generated image of a classroom
CoderSpaces: Tuesdays Winter 2023 (February 28, 2023 9:30am) https://events.umich.edu/event/103187 103187-21806265@events.umich.edu Event Begins: Tuesday, February 28, 2023 9:30am
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:15:11 -0500 2023-02-28T09:30:00-05:00 2023-02-28T11:00:00-05:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces Winter 2023 - weekly data science hubs via Zoom
CoderSpaces: Wednesdays Winter 2023 (March 1, 2023 1:30pm) https://events.umich.edu/event/103188 103188-21806281@events.umich.edu Event Begins: Wednesday, March 1, 2023 1:30pm
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:18:31 -0500 2023-03-01T13:30:00-05:00 2023-03-01T15:00:00-05:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces - weekly data science hubs via Zoom
TikTok, Boom Virtual Film Screening (March 6, 2023 12:00am) https://events.umich.edu/event/105817 105817-21813016@events.umich.edu Event Begins: Monday, March 6, 2023 12:00am
Location: Off Campus Location
Organized By: Information and Technology Services (ITS)

The Dissonance Event Series is proud to present viewing and discussion of TikTok, Boom, another film from Women Make Movies. Directed by Shalini Kantayya and nominated for the Grand Jury Prize at the 2022 Sundance Film Festival, TikTok, Boom examines the algorithmic, socio-political, economic, and cultural influences and impacts of TikTok.

The film will be available to view on PBS: https://www.pbs.org/independentlens/documentaries/tiktok-boom/

Dissonance will host a conversation with filmmaker Shalini Kantayya and a panel of U-M faculty and students on March 16 at 11 a.m. (https://events.umich.edu/event/104991)

TikTok, Boom Events Page: https://safecomputing.umich.edu/events/dissonance/TikTokBoom

Register to attend the March 16 virtual discussion: https://umich.zoom.us/webinar/register/WN_a7DS9uIcQdKpkVCdqDJNRQ
Add the event to your Google Calendar: https://calendar.google.com/calendar/u/0/r/eventedit/copy/NHFwNGRjODBuam5qOXNrNGZhdm84OGwyazkgdW1pY2guZWR1X2ZkczI0Z2V2cGE0MnY5NTc2bG5wZTJjbWxrQGc

ABOUT THE FILM
Dissecting one of the most influential platforms of the contemporary social media landscape, TikTok Boom examines the algorithmic, socio-political, economic, and cultural influences and impact of the history-making app. This rigorous exploration balances a genuine interest in the TikTok community and its innovative mechanics with a healthy skepticism around the security issues, global political challenges, and racial biases behind the platform. A cast of Gen Z subjects, helmed by influencer Feroza Aziz, remains at its center, making this one of the most needed and empathetic films exploring what it means to be a digital native.

DIRECTOR & PRODUCER: SHALINI KANTAYYA
Emmy-nominated filmmaker Shalini Kantayya directs fiction and nonfiction films that artfully marry the future of science with the future of story. Her latest film, TikTok, Boom, was nominated for the Grand Jury Prize at the 2022 Sundance Film Festival and was official selection at SXSW. Her critically-acclaimed 2020 Sundance film, Coded Bias, was broadcast nationally on PBS’s Independent Lens and globally on Netflix in April 2021. The film has been nominated for a Critics’ Choice, and an NAACP Image Award for Outstanding Documentary. The film won Best Director at the Social Impact Media Awards, and the Visionary Filmmaker Award at GlobeDocs. Shalini’s debut feature, Catching the Sun, released globally on Netflix on Earth Day 2016 with Executive Producer Leonardo DiCaprio and was named a New York Times Critics’ Pick.

Shalini directed for National Geographic television series Breakthrough ), Executive Produced by Ron Howard, and episodes for NOVA and YouTube Originals. She is a TED Fellow, a William J. Fulbright Scholar, and Concordia Studios Artist Fellow. She is an Associate of the UC Berkeley School of Journalism.

LINKS & RESOURCES
- Shalini Kantayya website: https://www.shalinikantayya.net/about
- National Geographic television series Breakthrough: https://www.nationalgeographic.com/tv/
- TED Fellow: https://www.youtube.com/watch?v=qVzNNZ6w-ls)
- Coded Bias - Dissonance Panel Discussion - April 15, 2021: https://safecomputing.umich.edu/events/dissonance/coded-bias-panel-discussion
- Women Make Movies: https://www.wmm.com/

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Film Screening Mon, 06 Mar 2023 18:18:22 -0500 2023-03-06T00:00:00-05:00 2023-03-06T23:59:00-05:00 Off Campus Location Information and Technology Services (ITS) Film Screening TikTok, Boom logo on black background with Sundance festival 2022 selection logo
TikTok, Boom Virtual Film Screening (March 7, 2023 12:00am) https://events.umich.edu/event/105817 105817-21813017@events.umich.edu Event Begins: Tuesday, March 7, 2023 12:00am
Location: Off Campus Location
Organized By: Information and Technology Services (ITS)

The Dissonance Event Series is proud to present viewing and discussion of TikTok, Boom, another film from Women Make Movies. Directed by Shalini Kantayya and nominated for the Grand Jury Prize at the 2022 Sundance Film Festival, TikTok, Boom examines the algorithmic, socio-political, economic, and cultural influences and impacts of TikTok.

The film will be available to view on PBS: https://www.pbs.org/independentlens/documentaries/tiktok-boom/

Dissonance will host a conversation with filmmaker Shalini Kantayya and a panel of U-M faculty and students on March 16 at 11 a.m. (https://events.umich.edu/event/104991)

TikTok, Boom Events Page: https://safecomputing.umich.edu/events/dissonance/TikTokBoom

Register to attend the March 16 virtual discussion: https://umich.zoom.us/webinar/register/WN_a7DS9uIcQdKpkVCdqDJNRQ
Add the event to your Google Calendar: https://calendar.google.com/calendar/u/0/r/eventedit/copy/NHFwNGRjODBuam5qOXNrNGZhdm84OGwyazkgdW1pY2guZWR1X2ZkczI0Z2V2cGE0MnY5NTc2bG5wZTJjbWxrQGc

ABOUT THE FILM
Dissecting one of the most influential platforms of the contemporary social media landscape, TikTok Boom examines the algorithmic, socio-political, economic, and cultural influences and impact of the history-making app. This rigorous exploration balances a genuine interest in the TikTok community and its innovative mechanics with a healthy skepticism around the security issues, global political challenges, and racial biases behind the platform. A cast of Gen Z subjects, helmed by influencer Feroza Aziz, remains at its center, making this one of the most needed and empathetic films exploring what it means to be a digital native.

DIRECTOR & PRODUCER: SHALINI KANTAYYA
Emmy-nominated filmmaker Shalini Kantayya directs fiction and nonfiction films that artfully marry the future of science with the future of story. Her latest film, TikTok, Boom, was nominated for the Grand Jury Prize at the 2022 Sundance Film Festival and was official selection at SXSW. Her critically-acclaimed 2020 Sundance film, Coded Bias, was broadcast nationally on PBS’s Independent Lens and globally on Netflix in April 2021. The film has been nominated for a Critics’ Choice, and an NAACP Image Award for Outstanding Documentary. The film won Best Director at the Social Impact Media Awards, and the Visionary Filmmaker Award at GlobeDocs. Shalini’s debut feature, Catching the Sun, released globally on Netflix on Earth Day 2016 with Executive Producer Leonardo DiCaprio and was named a New York Times Critics’ Pick.

Shalini directed for National Geographic television series Breakthrough ), Executive Produced by Ron Howard, and episodes for NOVA and YouTube Originals. She is a TED Fellow, a William J. Fulbright Scholar, and Concordia Studios Artist Fellow. She is an Associate of the UC Berkeley School of Journalism.

LINKS & RESOURCES
- Shalini Kantayya website: https://www.shalinikantayya.net/about
- National Geographic television series Breakthrough: https://www.nationalgeographic.com/tv/
- TED Fellow: https://www.youtube.com/watch?v=qVzNNZ6w-ls)
- Coded Bias - Dissonance Panel Discussion - April 15, 2021: https://safecomputing.umich.edu/events/dissonance/coded-bias-panel-discussion
- Women Make Movies: https://www.wmm.com/

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Film Screening Mon, 06 Mar 2023 18:18:22 -0500 2023-03-07T00:00:00-05:00 2023-03-07T23:59:00-05:00 Off Campus Location Information and Technology Services (ITS) Film Screening TikTok, Boom logo on black background with Sundance festival 2022 selection logo
CoderSpaces: Tuesdays Winter 2023 (March 7, 2023 9:30am) https://events.umich.edu/event/103187 103187-21806266@events.umich.edu Event Begins: Tuesday, March 7, 2023 9:30am
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:15:11 -0500 2023-03-07T09:30:00-05:00 2023-03-07T11:00:00-05:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces Winter 2023 - weekly data science hubs via Zoom
TikTok, Boom Virtual Film Screening (March 8, 2023 12:00am) https://events.umich.edu/event/105817 105817-21813018@events.umich.edu Event Begins: Wednesday, March 8, 2023 12:00am
Location: Off Campus Location
Organized By: Information and Technology Services (ITS)

The Dissonance Event Series is proud to present viewing and discussion of TikTok, Boom, another film from Women Make Movies. Directed by Shalini Kantayya and nominated for the Grand Jury Prize at the 2022 Sundance Film Festival, TikTok, Boom examines the algorithmic, socio-political, economic, and cultural influences and impacts of TikTok.

The film will be available to view on PBS: https://www.pbs.org/independentlens/documentaries/tiktok-boom/

Dissonance will host a conversation with filmmaker Shalini Kantayya and a panel of U-M faculty and students on March 16 at 11 a.m. (https://events.umich.edu/event/104991)

TikTok, Boom Events Page: https://safecomputing.umich.edu/events/dissonance/TikTokBoom

Register to attend the March 16 virtual discussion: https://umich.zoom.us/webinar/register/WN_a7DS9uIcQdKpkVCdqDJNRQ
Add the event to your Google Calendar: https://calendar.google.com/calendar/u/0/r/eventedit/copy/NHFwNGRjODBuam5qOXNrNGZhdm84OGwyazkgdW1pY2guZWR1X2ZkczI0Z2V2cGE0MnY5NTc2bG5wZTJjbWxrQGc

ABOUT THE FILM
Dissecting one of the most influential platforms of the contemporary social media landscape, TikTok Boom examines the algorithmic, socio-political, economic, and cultural influences and impact of the history-making app. This rigorous exploration balances a genuine interest in the TikTok community and its innovative mechanics with a healthy skepticism around the security issues, global political challenges, and racial biases behind the platform. A cast of Gen Z subjects, helmed by influencer Feroza Aziz, remains at its center, making this one of the most needed and empathetic films exploring what it means to be a digital native.

DIRECTOR & PRODUCER: SHALINI KANTAYYA
Emmy-nominated filmmaker Shalini Kantayya directs fiction and nonfiction films that artfully marry the future of science with the future of story. Her latest film, TikTok, Boom, was nominated for the Grand Jury Prize at the 2022 Sundance Film Festival and was official selection at SXSW. Her critically-acclaimed 2020 Sundance film, Coded Bias, was broadcast nationally on PBS’s Independent Lens and globally on Netflix in April 2021. The film has been nominated for a Critics’ Choice, and an NAACP Image Award for Outstanding Documentary. The film won Best Director at the Social Impact Media Awards, and the Visionary Filmmaker Award at GlobeDocs. Shalini’s debut feature, Catching the Sun, released globally on Netflix on Earth Day 2016 with Executive Producer Leonardo DiCaprio and was named a New York Times Critics’ Pick.

Shalini directed for National Geographic television series Breakthrough ), Executive Produced by Ron Howard, and episodes for NOVA and YouTube Originals. She is a TED Fellow, a William J. Fulbright Scholar, and Concordia Studios Artist Fellow. She is an Associate of the UC Berkeley School of Journalism.

LINKS & RESOURCES
- Shalini Kantayya website: https://www.shalinikantayya.net/about
- National Geographic television series Breakthrough: https://www.nationalgeographic.com/tv/
- TED Fellow: https://www.youtube.com/watch?v=qVzNNZ6w-ls)
- Coded Bias - Dissonance Panel Discussion - April 15, 2021: https://safecomputing.umich.edu/events/dissonance/coded-bias-panel-discussion
- Women Make Movies: https://www.wmm.com/

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Film Screening Mon, 06 Mar 2023 18:18:22 -0500 2023-03-08T00:00:00-05:00 2023-03-08T23:59:00-05:00 Off Campus Location Information and Technology Services (ITS) Film Screening TikTok, Boom logo on black background with Sundance festival 2022 selection logo
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.

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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
CoderSpaces: Wednesdays Winter 2023 (March 8, 2023 1:30pm) https://events.umich.edu/event/103188 103188-21806282@events.umich.edu Event Begins: Wednesday, March 8, 2023 1:30pm
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

]]>
Workshop / Seminar Tue, 10 Jan 2023 16:18:31 -0500 2023-03-08T13:30:00-05:00 2023-03-08T15:00:00-05:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces - weekly data science hubs via Zoom
TikTok, Boom Virtual Film Screening (March 9, 2023 12:00am) https://events.umich.edu/event/105817 105817-21813019@events.umich.edu Event Begins: Thursday, March 9, 2023 12:00am
Location: Off Campus Location
Organized By: Information and Technology Services (ITS)

The Dissonance Event Series is proud to present viewing and discussion of TikTok, Boom, another film from Women Make Movies. Directed by Shalini Kantayya and nominated for the Grand Jury Prize at the 2022 Sundance Film Festival, TikTok, Boom examines the algorithmic, socio-political, economic, and cultural influences and impacts of TikTok.

The film will be available to view on PBS: https://www.pbs.org/independentlens/documentaries/tiktok-boom/

Dissonance will host a conversation with filmmaker Shalini Kantayya and a panel of U-M faculty and students on March 16 at 11 a.m. (https://events.umich.edu/event/104991)

TikTok, Boom Events Page: https://safecomputing.umich.edu/events/dissonance/TikTokBoom

Register to attend the March 16 virtual discussion: https://umich.zoom.us/webinar/register/WN_a7DS9uIcQdKpkVCdqDJNRQ
Add the event to your Google Calendar: https://calendar.google.com/calendar/u/0/r/eventedit/copy/NHFwNGRjODBuam5qOXNrNGZhdm84OGwyazkgdW1pY2guZWR1X2ZkczI0Z2V2cGE0MnY5NTc2bG5wZTJjbWxrQGc

ABOUT THE FILM
Dissecting one of the most influential platforms of the contemporary social media landscape, TikTok Boom examines the algorithmic, socio-political, economic, and cultural influences and impact of the history-making app. This rigorous exploration balances a genuine interest in the TikTok community and its innovative mechanics with a healthy skepticism around the security issues, global political challenges, and racial biases behind the platform. A cast of Gen Z subjects, helmed by influencer Feroza Aziz, remains at its center, making this one of the most needed and empathetic films exploring what it means to be a digital native.

DIRECTOR & PRODUCER: SHALINI KANTAYYA
Emmy-nominated filmmaker Shalini Kantayya directs fiction and nonfiction films that artfully marry the future of science with the future of story. Her latest film, TikTok, Boom, was nominated for the Grand Jury Prize at the 2022 Sundance Film Festival and was official selection at SXSW. Her critically-acclaimed 2020 Sundance film, Coded Bias, was broadcast nationally on PBS’s Independent Lens and globally on Netflix in April 2021. The film has been nominated for a Critics’ Choice, and an NAACP Image Award for Outstanding Documentary. The film won Best Director at the Social Impact Media Awards, and the Visionary Filmmaker Award at GlobeDocs. Shalini’s debut feature, Catching the Sun, released globally on Netflix on Earth Day 2016 with Executive Producer Leonardo DiCaprio and was named a New York Times Critics’ Pick.

Shalini directed for National Geographic television series Breakthrough ), Executive Produced by Ron Howard, and episodes for NOVA and YouTube Originals. She is a TED Fellow, a William J. Fulbright Scholar, and Concordia Studios Artist Fellow. She is an Associate of the UC Berkeley School of Journalism.

LINKS & RESOURCES
- Shalini Kantayya website: https://www.shalinikantayya.net/about
- National Geographic television series Breakthrough: https://www.nationalgeographic.com/tv/
- TED Fellow: https://www.youtube.com/watch?v=qVzNNZ6w-ls)
- Coded Bias - Dissonance Panel Discussion - April 15, 2021: https://safecomputing.umich.edu/events/dissonance/coded-bias-panel-discussion
- Women Make Movies: https://www.wmm.com/

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Film Screening Mon, 06 Mar 2023 18:18:22 -0500 2023-03-09T00:00:00-05:00 2023-03-09T23:59:00-05:00 Off Campus Location Information and Technology Services (ITS) Film Screening TikTok, Boom logo on black background with Sundance festival 2022 selection logo
TikTok, Boom Virtual Film Screening (March 10, 2023 12:00am) https://events.umich.edu/event/105817 105817-21813020@events.umich.edu Event Begins: Friday, March 10, 2023 12:00am
Location: Off Campus Location
Organized By: Information and Technology Services (ITS)

The Dissonance Event Series is proud to present viewing and discussion of TikTok, Boom, another film from Women Make Movies. Directed by Shalini Kantayya and nominated for the Grand Jury Prize at the 2022 Sundance Film Festival, TikTok, Boom examines the algorithmic, socio-political, economic, and cultural influences and impacts of TikTok.

The film will be available to view on PBS: https://www.pbs.org/independentlens/documentaries/tiktok-boom/

Dissonance will host a conversation with filmmaker Shalini Kantayya and a panel of U-M faculty and students on March 16 at 11 a.m. (https://events.umich.edu/event/104991)

TikTok, Boom Events Page: https://safecomputing.umich.edu/events/dissonance/TikTokBoom

Register to attend the March 16 virtual discussion: https://umich.zoom.us/webinar/register/WN_a7DS9uIcQdKpkVCdqDJNRQ
Add the event to your Google Calendar: https://calendar.google.com/calendar/u/0/r/eventedit/copy/NHFwNGRjODBuam5qOXNrNGZhdm84OGwyazkgdW1pY2guZWR1X2ZkczI0Z2V2cGE0MnY5NTc2bG5wZTJjbWxrQGc

ABOUT THE FILM
Dissecting one of the most influential platforms of the contemporary social media landscape, TikTok Boom examines the algorithmic, socio-political, economic, and cultural influences and impact of the history-making app. This rigorous exploration balances a genuine interest in the TikTok community and its innovative mechanics with a healthy skepticism around the security issues, global political challenges, and racial biases behind the platform. A cast of Gen Z subjects, helmed by influencer Feroza Aziz, remains at its center, making this one of the most needed and empathetic films exploring what it means to be a digital native.

DIRECTOR & PRODUCER: SHALINI KANTAYYA
Emmy-nominated filmmaker Shalini Kantayya directs fiction and nonfiction films that artfully marry the future of science with the future of story. Her latest film, TikTok, Boom, was nominated for the Grand Jury Prize at the 2022 Sundance Film Festival and was official selection at SXSW. Her critically-acclaimed 2020 Sundance film, Coded Bias, was broadcast nationally on PBS’s Independent Lens and globally on Netflix in April 2021. The film has been nominated for a Critics’ Choice, and an NAACP Image Award for Outstanding Documentary. The film won Best Director at the Social Impact Media Awards, and the Visionary Filmmaker Award at GlobeDocs. Shalini’s debut feature, Catching the Sun, released globally on Netflix on Earth Day 2016 with Executive Producer Leonardo DiCaprio and was named a New York Times Critics’ Pick.

Shalini directed for National Geographic television series Breakthrough ), Executive Produced by Ron Howard, and episodes for NOVA and YouTube Originals. She is a TED Fellow, a William J. Fulbright Scholar, and Concordia Studios Artist Fellow. She is an Associate of the UC Berkeley School of Journalism.

LINKS & RESOURCES
- Shalini Kantayya website: https://www.shalinikantayya.net/about
- National Geographic television series Breakthrough: https://www.nationalgeographic.com/tv/
- TED Fellow: https://www.youtube.com/watch?v=qVzNNZ6w-ls)
- Coded Bias - Dissonance Panel Discussion - April 15, 2021: https://safecomputing.umich.edu/events/dissonance/coded-bias-panel-discussion
- Women Make Movies: https://www.wmm.com/

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Film Screening Mon, 06 Mar 2023 18:18:22 -0500 2023-03-10T00:00:00-05:00 2023-03-10T23:59:00-05:00 Off Campus Location Information and Technology Services (ITS) Film Screening TikTok, Boom logo on black background with Sundance festival 2022 selection logo
TikTok, Boom Virtual Film Screening (March 11, 2023 12:00am) https://events.umich.edu/event/105817 105817-21813021@events.umich.edu Event Begins: Saturday, March 11, 2023 12:00am
Location: Off Campus Location
Organized By: Information and Technology Services (ITS)

The Dissonance Event Series is proud to present viewing and discussion of TikTok, Boom, another film from Women Make Movies. Directed by Shalini Kantayya and nominated for the Grand Jury Prize at the 2022 Sundance Film Festival, TikTok, Boom examines the algorithmic, socio-political, economic, and cultural influences and impacts of TikTok.

The film will be available to view on PBS: https://www.pbs.org/independentlens/documentaries/tiktok-boom/

Dissonance will host a conversation with filmmaker Shalini Kantayya and a panel of U-M faculty and students on March 16 at 11 a.m. (https://events.umich.edu/event/104991)

TikTok, Boom Events Page: https://safecomputing.umich.edu/events/dissonance/TikTokBoom

Register to attend the March 16 virtual discussion: https://umich.zoom.us/webinar/register/WN_a7DS9uIcQdKpkVCdqDJNRQ
Add the event to your Google Calendar: https://calendar.google.com/calendar/u/0/r/eventedit/copy/NHFwNGRjODBuam5qOXNrNGZhdm84OGwyazkgdW1pY2guZWR1X2ZkczI0Z2V2cGE0MnY5NTc2bG5wZTJjbWxrQGc

ABOUT THE FILM
Dissecting one of the most influential platforms of the contemporary social media landscape, TikTok Boom examines the algorithmic, socio-political, economic, and cultural influences and impact of the history-making app. This rigorous exploration balances a genuine interest in the TikTok community and its innovative mechanics with a healthy skepticism around the security issues, global political challenges, and racial biases behind the platform. A cast of Gen Z subjects, helmed by influencer Feroza Aziz, remains at its center, making this one of the most needed and empathetic films exploring what it means to be a digital native.

DIRECTOR & PRODUCER: SHALINI KANTAYYA
Emmy-nominated filmmaker Shalini Kantayya directs fiction and nonfiction films that artfully marry the future of science with the future of story. Her latest film, TikTok, Boom, was nominated for the Grand Jury Prize at the 2022 Sundance Film Festival and was official selection at SXSW. Her critically-acclaimed 2020 Sundance film, Coded Bias, was broadcast nationally on PBS’s Independent Lens and globally on Netflix in April 2021. The film has been nominated for a Critics’ Choice, and an NAACP Image Award for Outstanding Documentary. The film won Best Director at the Social Impact Media Awards, and the Visionary Filmmaker Award at GlobeDocs. Shalini’s debut feature, Catching the Sun, released globally on Netflix on Earth Day 2016 with Executive Producer Leonardo DiCaprio and was named a New York Times Critics’ Pick.

Shalini directed for National Geographic television series Breakthrough ), Executive Produced by Ron Howard, and episodes for NOVA and YouTube Originals. She is a TED Fellow, a William J. Fulbright Scholar, and Concordia Studios Artist Fellow. She is an Associate of the UC Berkeley School of Journalism.

LINKS & RESOURCES
- Shalini Kantayya website: https://www.shalinikantayya.net/about
- National Geographic television series Breakthrough: https://www.nationalgeographic.com/tv/
- TED Fellow: https://www.youtube.com/watch?v=qVzNNZ6w-ls)
- Coded Bias - Dissonance Panel Discussion - April 15, 2021: https://safecomputing.umich.edu/events/dissonance/coded-bias-panel-discussion
- Women Make Movies: https://www.wmm.com/

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Film Screening Mon, 06 Mar 2023 18:18:22 -0500 2023-03-11T00:00:00-05:00 2023-03-11T23:59:00-05:00 Off Campus Location Information and Technology Services (ITS) Film Screening TikTok, Boom logo on black background with Sundance festival 2022 selection logo
TikTok, Boom Virtual Film Screening (March 12, 2023 12:00am) https://events.umich.edu/event/105817 105817-21813022@events.umich.edu Event Begins: Sunday, March 12, 2023 12:00am
Location: Off Campus Location
Organized By: Information and Technology Services (ITS)

The Dissonance Event Series is proud to present viewing and discussion of TikTok, Boom, another film from Women Make Movies. Directed by Shalini Kantayya and nominated for the Grand Jury Prize at the 2022 Sundance Film Festival, TikTok, Boom examines the algorithmic, socio-political, economic, and cultural influences and impacts of TikTok.

The film will be available to view on PBS: https://www.pbs.org/independentlens/documentaries/tiktok-boom/

Dissonance will host a conversation with filmmaker Shalini Kantayya and a panel of U-M faculty and students on March 16 at 11 a.m. (https://events.umich.edu/event/104991)

TikTok, Boom Events Page: https://safecomputing.umich.edu/events/dissonance/TikTokBoom

Register to attend the March 16 virtual discussion: https://umich.zoom.us/webinar/register/WN_a7DS9uIcQdKpkVCdqDJNRQ
Add the event to your Google Calendar: https://calendar.google.com/calendar/u/0/r/eventedit/copy/NHFwNGRjODBuam5qOXNrNGZhdm84OGwyazkgdW1pY2guZWR1X2ZkczI0Z2V2cGE0MnY5NTc2bG5wZTJjbWxrQGc

ABOUT THE FILM
Dissecting one of the most influential platforms of the contemporary social media landscape, TikTok Boom examines the algorithmic, socio-political, economic, and cultural influences and impact of the history-making app. This rigorous exploration balances a genuine interest in the TikTok community and its innovative mechanics with a healthy skepticism around the security issues, global political challenges, and racial biases behind the platform. A cast of Gen Z subjects, helmed by influencer Feroza Aziz, remains at its center, making this one of the most needed and empathetic films exploring what it means to be a digital native.

DIRECTOR & PRODUCER: SHALINI KANTAYYA
Emmy-nominated filmmaker Shalini Kantayya directs fiction and nonfiction films that artfully marry the future of science with the future of story. Her latest film, TikTok, Boom, was nominated for the Grand Jury Prize at the 2022 Sundance Film Festival and was official selection at SXSW. Her critically-acclaimed 2020 Sundance film, Coded Bias, was broadcast nationally on PBS’s Independent Lens and globally on Netflix in April 2021. The film has been nominated for a Critics’ Choice, and an NAACP Image Award for Outstanding Documentary. The film won Best Director at the Social Impact Media Awards, and the Visionary Filmmaker Award at GlobeDocs. Shalini’s debut feature, Catching the Sun, released globally on Netflix on Earth Day 2016 with Executive Producer Leonardo DiCaprio and was named a New York Times Critics’ Pick.

Shalini directed for National Geographic television series Breakthrough ), Executive Produced by Ron Howard, and episodes for NOVA and YouTube Originals. She is a TED Fellow, a William J. Fulbright Scholar, and Concordia Studios Artist Fellow. She is an Associate of the UC Berkeley School of Journalism.

LINKS & RESOURCES
- Shalini Kantayya website: https://www.shalinikantayya.net/about
- National Geographic television series Breakthrough: https://www.nationalgeographic.com/tv/
- TED Fellow: https://www.youtube.com/watch?v=qVzNNZ6w-ls)
- Coded Bias - Dissonance Panel Discussion - April 15, 2021: https://safecomputing.umich.edu/events/dissonance/coded-bias-panel-discussion
- Women Make Movies: https://www.wmm.com/

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Film Screening Mon, 06 Mar 2023 18:18:22 -0500 2023-03-12T00:00:00-05:00 2023-03-12T23:59:00-04:00 Off Campus Location Information and Technology Services (ITS) Film Screening TikTok, Boom logo on black background with Sundance festival 2022 selection logo
TikTok, Boom Virtual Film Screening (March 13, 2023 12:00am) https://events.umich.edu/event/105817 105817-21813023@events.umich.edu Event Begins: Monday, March 13, 2023 12:00am
Location: Off Campus Location
Organized By: Information and Technology Services (ITS)

The Dissonance Event Series is proud to present viewing and discussion of TikTok, Boom, another film from Women Make Movies. Directed by Shalini Kantayya and nominated for the Grand Jury Prize at the 2022 Sundance Film Festival, TikTok, Boom examines the algorithmic, socio-political, economic, and cultural influences and impacts of TikTok.

The film will be available to view on PBS: https://www.pbs.org/independentlens/documentaries/tiktok-boom/

Dissonance will host a conversation with filmmaker Shalini Kantayya and a panel of U-M faculty and students on March 16 at 11 a.m. (https://events.umich.edu/event/104991)

TikTok, Boom Events Page: https://safecomputing.umich.edu/events/dissonance/TikTokBoom

Register to attend the March 16 virtual discussion: https://umich.zoom.us/webinar/register/WN_a7DS9uIcQdKpkVCdqDJNRQ
Add the event to your Google Calendar: https://calendar.google.com/calendar/u/0/r/eventedit/copy/NHFwNGRjODBuam5qOXNrNGZhdm84OGwyazkgdW1pY2guZWR1X2ZkczI0Z2V2cGE0MnY5NTc2bG5wZTJjbWxrQGc

ABOUT THE FILM
Dissecting one of the most influential platforms of the contemporary social media landscape, TikTok Boom examines the algorithmic, socio-political, economic, and cultural influences and impact of the history-making app. This rigorous exploration balances a genuine interest in the TikTok community and its innovative mechanics with a healthy skepticism around the security issues, global political challenges, and racial biases behind the platform. A cast of Gen Z subjects, helmed by influencer Feroza Aziz, remains at its center, making this one of the most needed and empathetic films exploring what it means to be a digital native.

DIRECTOR & PRODUCER: SHALINI KANTAYYA
Emmy-nominated filmmaker Shalini Kantayya directs fiction and nonfiction films that artfully marry the future of science with the future of story. Her latest film, TikTok, Boom, was nominated for the Grand Jury Prize at the 2022 Sundance Film Festival and was official selection at SXSW. Her critically-acclaimed 2020 Sundance film, Coded Bias, was broadcast nationally on PBS’s Independent Lens and globally on Netflix in April 2021. The film has been nominated for a Critics’ Choice, and an NAACP Image Award for Outstanding Documentary. The film won Best Director at the Social Impact Media Awards, and the Visionary Filmmaker Award at GlobeDocs. Shalini’s debut feature, Catching the Sun, released globally on Netflix on Earth Day 2016 with Executive Producer Leonardo DiCaprio and was named a New York Times Critics’ Pick.

Shalini directed for National Geographic television series Breakthrough ), Executive Produced by Ron Howard, and episodes for NOVA and YouTube Originals. She is a TED Fellow, a William J. Fulbright Scholar, and Concordia Studios Artist Fellow. She is an Associate of the UC Berkeley School of Journalism.

LINKS & RESOURCES
- Shalini Kantayya website: https://www.shalinikantayya.net/about
- National Geographic television series Breakthrough: https://www.nationalgeographic.com/tv/
- TED Fellow: https://www.youtube.com/watch?v=qVzNNZ6w-ls)
- Coded Bias - Dissonance Panel Discussion - April 15, 2021: https://safecomputing.umich.edu/events/dissonance/coded-bias-panel-discussion
- Women Make Movies: https://www.wmm.com/

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Film Screening Mon, 06 Mar 2023 18:18:22 -0500 2023-03-13T00:00:00-04:00 2023-03-13T23:59:00-04:00 Off Campus Location Information and Technology Services (ITS) Film Screening TikTok, Boom logo on black background with Sundance festival 2022 selection logo
TikTok, Boom Virtual Film Screening (March 14, 2023 12:00am) https://events.umich.edu/event/105817 105817-21813024@events.umich.edu Event Begins: Tuesday, March 14, 2023 12:00am
Location: Off Campus Location
Organized By: Information and Technology Services (ITS)

The Dissonance Event Series is proud to present viewing and discussion of TikTok, Boom, another film from Women Make Movies. Directed by Shalini Kantayya and nominated for the Grand Jury Prize at the 2022 Sundance Film Festival, TikTok, Boom examines the algorithmic, socio-political, economic, and cultural influences and impacts of TikTok.

The film will be available to view on PBS: https://www.pbs.org/independentlens/documentaries/tiktok-boom/

Dissonance will host a conversation with filmmaker Shalini Kantayya and a panel of U-M faculty and students on March 16 at 11 a.m. (https://events.umich.edu/event/104991)

TikTok, Boom Events Page: https://safecomputing.umich.edu/events/dissonance/TikTokBoom

Register to attend the March 16 virtual discussion: https://umich.zoom.us/webinar/register/WN_a7DS9uIcQdKpkVCdqDJNRQ
Add the event to your Google Calendar: https://calendar.google.com/calendar/u/0/r/eventedit/copy/NHFwNGRjODBuam5qOXNrNGZhdm84OGwyazkgdW1pY2guZWR1X2ZkczI0Z2V2cGE0MnY5NTc2bG5wZTJjbWxrQGc

ABOUT THE FILM
Dissecting one of the most influential platforms of the contemporary social media landscape, TikTok Boom examines the algorithmic, socio-political, economic, and cultural influences and impact of the history-making app. This rigorous exploration balances a genuine interest in the TikTok community and its innovative mechanics with a healthy skepticism around the security issues, global political challenges, and racial biases behind the platform. A cast of Gen Z subjects, helmed by influencer Feroza Aziz, remains at its center, making this one of the most needed and empathetic films exploring what it means to be a digital native.

DIRECTOR & PRODUCER: SHALINI KANTAYYA
Emmy-nominated filmmaker Shalini Kantayya directs fiction and nonfiction films that artfully marry the future of science with the future of story. Her latest film, TikTok, Boom, was nominated for the Grand Jury Prize at the 2022 Sundance Film Festival and was official selection at SXSW. Her critically-acclaimed 2020 Sundance film, Coded Bias, was broadcast nationally on PBS’s Independent Lens and globally on Netflix in April 2021. The film has been nominated for a Critics’ Choice, and an NAACP Image Award for Outstanding Documentary. The film won Best Director at the Social Impact Media Awards, and the Visionary Filmmaker Award at GlobeDocs. Shalini’s debut feature, Catching the Sun, released globally on Netflix on Earth Day 2016 with Executive Producer Leonardo DiCaprio and was named a New York Times Critics’ Pick.

Shalini directed for National Geographic television series Breakthrough ), Executive Produced by Ron Howard, and episodes for NOVA and YouTube Originals. She is a TED Fellow, a William J. Fulbright Scholar, and Concordia Studios Artist Fellow. She is an Associate of the UC Berkeley School of Journalism.

LINKS & RESOURCES
- Shalini Kantayya website: https://www.shalinikantayya.net/about
- National Geographic television series Breakthrough: https://www.nationalgeographic.com/tv/
- TED Fellow: https://www.youtube.com/watch?v=qVzNNZ6w-ls)
- Coded Bias - Dissonance Panel Discussion - April 15, 2021: https://safecomputing.umich.edu/events/dissonance/coded-bias-panel-discussion
- Women Make Movies: https://www.wmm.com/

]]>
Film Screening Mon, 06 Mar 2023 18:18:22 -0500 2023-03-14T00:00:00-04:00 2023-03-14T23:59:00-04:00 Off Campus Location Information and Technology Services (ITS) Film Screening TikTok, Boom logo on black background with Sundance festival 2022 selection logo
CoderSpaces: Tuesdays Winter 2023 (March 14, 2023 9:30am) https://events.umich.edu/event/103187 103187-21806267@events.umich.edu Event Begins: Tuesday, March 14, 2023 9:30am
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:15:11 -0500 2023-03-14T09:30:00-04:00 2023-03-14T11:00:00-04:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces Winter 2023 - weekly data science hubs via Zoom
TikTok, Boom Virtual Film Screening (March 15, 2023 12:00am) https://events.umich.edu/event/105817 105817-21813025@events.umich.edu Event Begins: Wednesday, March 15, 2023 12:00am
Location: Off Campus Location
Organized By: Information and Technology Services (ITS)

The Dissonance Event Series is proud to present viewing and discussion of TikTok, Boom, another film from Women Make Movies. Directed by Shalini Kantayya and nominated for the Grand Jury Prize at the 2022 Sundance Film Festival, TikTok, Boom examines the algorithmic, socio-political, economic, and cultural influences and impacts of TikTok.

The film will be available to view on PBS: https://www.pbs.org/independentlens/documentaries/tiktok-boom/

Dissonance will host a conversation with filmmaker Shalini Kantayya and a panel of U-M faculty and students on March 16 at 11 a.m. (https://events.umich.edu/event/104991)

TikTok, Boom Events Page: https://safecomputing.umich.edu/events/dissonance/TikTokBoom

Register to attend the March 16 virtual discussion: https://umich.zoom.us/webinar/register/WN_a7DS9uIcQdKpkVCdqDJNRQ
Add the event to your Google Calendar: https://calendar.google.com/calendar/u/0/r/eventedit/copy/NHFwNGRjODBuam5qOXNrNGZhdm84OGwyazkgdW1pY2guZWR1X2ZkczI0Z2V2cGE0MnY5NTc2bG5wZTJjbWxrQGc

ABOUT THE FILM
Dissecting one of the most influential platforms of the contemporary social media landscape, TikTok Boom examines the algorithmic, socio-political, economic, and cultural influences and impact of the history-making app. This rigorous exploration balances a genuine interest in the TikTok community and its innovative mechanics with a healthy skepticism around the security issues, global political challenges, and racial biases behind the platform. A cast of Gen Z subjects, helmed by influencer Feroza Aziz, remains at its center, making this one of the most needed and empathetic films exploring what it means to be a digital native.

DIRECTOR & PRODUCER: SHALINI KANTAYYA
Emmy-nominated filmmaker Shalini Kantayya directs fiction and nonfiction films that artfully marry the future of science with the future of story. Her latest film, TikTok, Boom, was nominated for the Grand Jury Prize at the 2022 Sundance Film Festival and was official selection at SXSW. Her critically-acclaimed 2020 Sundance film, Coded Bias, was broadcast nationally on PBS’s Independent Lens and globally on Netflix in April 2021. The film has been nominated for a Critics’ Choice, and an NAACP Image Award for Outstanding Documentary. The film won Best Director at the Social Impact Media Awards, and the Visionary Filmmaker Award at GlobeDocs. Shalini’s debut feature, Catching the Sun, released globally on Netflix on Earth Day 2016 with Executive Producer Leonardo DiCaprio and was named a New York Times Critics’ Pick.

Shalini directed for National Geographic television series Breakthrough ), Executive Produced by Ron Howard, and episodes for NOVA and YouTube Originals. She is a TED Fellow, a William J. Fulbright Scholar, and Concordia Studios Artist Fellow. She is an Associate of the UC Berkeley School of Journalism.

LINKS & RESOURCES
- Shalini Kantayya website: https://www.shalinikantayya.net/about
- National Geographic television series Breakthrough: https://www.nationalgeographic.com/tv/
- TED Fellow: https://www.youtube.com/watch?v=qVzNNZ6w-ls)
- Coded Bias - Dissonance Panel Discussion - April 15, 2021: https://safecomputing.umich.edu/events/dissonance/coded-bias-panel-discussion
- Women Make Movies: https://www.wmm.com/

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Film Screening Mon, 06 Mar 2023 18:18:22 -0500 2023-03-15T00:00:00-04:00 2023-03-15T23:59:00-04:00 Off Campus Location Information and Technology Services (ITS) Film Screening TikTok, Boom logo on black background with Sundance festival 2022 selection logo
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.

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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
CoderSpaces: Wednesdays Winter 2023 (March 15, 2023 1:30pm) https://events.umich.edu/event/103188 103188-21806283@events.umich.edu Event Begins: Wednesday, March 15, 2023 1:30pm
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:18:31 -0500 2023-03-15T13:30:00-04:00 2023-03-15T15:00:00-04:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces - weekly data science hubs via Zoom
TikTok, Boom - Conversation with Director, Shalini Kantayya and U-M Panel (March 16, 2023 11:00am) https://events.umich.edu/event/104991 104991-21810544@events.umich.edu Event Begins: Thursday, March 16, 2023 11:00am
Location: Off Campus Location
Organized By: Information and Technology Services (ITS)

Join the Dissonance Event Series and participate in a discussion with the director of TikTok Boom, Emmy-nominated filmmaker Shalini Kantayya, along with a panel of U-M faculty and students. TikTok, Boom examines the algorithmic, socio-political, economic, and cultural influences and impacts of TikTok and was nominated for the Grand Jury Prize at the 2022 Sundance Film Festival.

The film will be available to view on PBS: https://www.pbs.org/independentlens/documentaries/tiktok-boom/

TikTok, Boom Events Page: https://safecomputing.umich.edu/events/dissonance/TikTokBoom

Register to attend the March 16 virtual discussion: https://umich.zoom.us/webinar/register/WN_a7DS9uIcQdKpkVCdqDJNRQ

Add the event to your Google Calendar: https://calendar.google.com/calendar/u/0/r/eventedit/copy/NHFwNGRjODBuam5qOXNrNGZhdm84OGwyazkgdW1pY2guZWR1X2ZkczI0Z2V2cGE0MnY5NTc2bG5wZTJjbWxrQGc

ABOUT THE FILM
Dissecting one of the most influential platforms of the contemporary social media landscape, TikTok Boom examines the algorithmic, socio-political, economic, and cultural influences and impact of the history-making app. This rigorous exploration balances a genuine interest in the TikTok community and its innovative mechanics with a healthy skepticism around the security issues, global political challenges, and racial biases behind the platform. A cast of Gen Z subjects, helmed by influencer Feroza Aziz, remains at its center, making this one of the most needed and empathetic films exploring what it means to be a digital native.

DIRECTOR & PRODUCER: SHALINI KANTAYYA
Emmy-nominated filmmaker Shalini Kantayya directs fiction and nonfiction films that artfully marry the future of science with the future of story. Her latest film, TikTok, Boom, was nominated for the Grand Jury Prize at the 2022 Sundance Film Festival and was official selection at SXSW. Her critically-acclaimed 2020 Sundance film, Coded Bias, was broadcast nationally on PBS’s Independent Lens and globally on Netflix in April 2021. The film has been nominated for a Critics’ Choice, and an NAACP Image Award for Outstanding Documentary. The film won Best Director at the Social Impact Media Awards, and the Visionary Filmmaker Award at GlobeDocs. Shalini’s debut feature, Catching the Sun, released globally on Netflix on Earth Day 2016 with Executive Producer Leonardo DiCaprio and was named a New York Times Critics’ Pick.

Shalini directed for National Geographic television series Breakthrough ), Executive Produced by Ron Howard, and episodes for NOVA and YouTube Originals. She is a TED Fellow, a William J. Fulbright Scholar, and Concordia Studios Artist Fellow. She is an Associate of the UC Berkeley School of Journalism.

LINKS & RESOURCES
- Shalini Kantayya website: https://www.shalinikantayya.net/about
- National Geographic television series Breakthrough: https://www.nationalgeographic.com/tv/
- TED Fellow: https://www.youtube.com/watch?v=qVzNNZ6w-ls)
- Coded Bias - Dissonance Panel Discussion - April 15, 2021: https://safecomputing.umich.edu/events/dissonance/coded-bias-panel-discussion
- Women Make Movies: https://www.wmm.com

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Lecture / Discussion Thu, 09 Mar 2023 13:54:26 -0500 2023-03-16T11:00:00-04:00 2023-03-16T12:00:00-04:00 Off Campus Location Information and Technology Services (ITS) Lecture / Discussion TikTok, Boom logo on black background with Sundance festival 2022 selection logo
CoderSpaces: Tuesdays Winter 2023 (March 21, 2023 9:30am) https://events.umich.edu/event/103187 103187-21806268@events.umich.edu Event Begins: Tuesday, March 21, 2023 9:30am
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:15:11 -0500 2023-03-21T09:30:00-04:00 2023-03-21T11:00:00-04:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces Winter 2023 - weekly data science hubs via Zoom
CoderSpaces: Wednesdays Winter 2023 (March 22, 2023 1:30pm) https://events.umich.edu/event/103188 103188-21806284@events.umich.edu Event Begins: Wednesday, March 22, 2023 1:30pm
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:18:31 -0500 2023-03-22T13:30:00-04:00 2023-03-22T15:00:00-04:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces - weekly data science hubs via Zoom
LHS Collaboratory (March 23, 2023 12:00pm) https://events.umich.edu/event/105035 105035-21810617@events.umich.edu Event Begins: Thursday, March 23, 2023 12:00pm
Location: Off Campus Location
Organized By: Department of Learning Health Sciences

Speaker:
Thomas R. Campion, Jr., Ph.D., FACMI, FAMIA
Chief Research Informatics Officer
Associate Professor of Research in Population Health Sciences
Weill Cornell Medicine

Clinical and translational investigators need patient data, especially from electronic health record (EHR) systems, to conduct research, but optimal approaches are unknown. This talk explores an approach for supporting different types of investigators and study designs by matching investigators with informatics tools and services.

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Lecture / Discussion Wed, 15 Feb 2023 23:51:27 -0500 2023-03-23T12:00:00-04:00 2023-03-23T13:30:00-04:00 Off Campus Location Department of Learning Health Sciences Lecture / Discussion LHS Collaboratory logo
CoderSpaces: Tuesdays Winter 2023 (March 28, 2023 9:30am) https://events.umich.edu/event/103187 103187-21806269@events.umich.edu Event Begins: Tuesday, March 28, 2023 9:30am
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:15:11 -0500 2023-03-28T09:30:00-04:00 2023-03-28T11:00:00-04:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces Winter 2023 - weekly data science hubs via Zoom
CoderSpaces: Wednesdays Winter 2023 (March 29, 2023 1:30pm) https://events.umich.edu/event/103188 103188-21806285@events.umich.edu Event Begins: Wednesday, March 29, 2023 1:30pm
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:18:31 -0500 2023-03-29T13:30:00-04:00 2023-03-29T15:00:00-04:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces - weekly data science hubs via Zoom
U-M AI in Science and Engineering Day (April 3, 2023 8:45am) https://events.umich.edu/event/104375 104375-21808976@events.umich.edu Event Begins: Monday, April 3, 2023 8:45am
Location: Palmer Commons
Organized By: Michigan Institute for Data Science

At this colloquium, visiting and local scholars, as well as the MIDAS Eric and Wendy Schmidt AI in Science and Engineering Fellows, will share their expertise about the implementation of AI in Science and Engineering.

The goal of this session is to enable more faculty and other researchers to adopt AI methods in their research.
All are welcome to attend.
Registration in advance is strongly recommended - Register at https://forms.gle/WUcCwUy1eghBBDAH8

Speakers:
Sara Beery: MIT EECS’ Faculty of AI and Decision Making, MIT CSAIL, and Visiting Researcher at Google
Yang Chen: Assistant Professor of Statistics, Research Assistant Professor for MIDAS, University of Michigan
Jeffrey Fessler: William L. Root Collegiate Professor of EECS, College of Engineering, University of Michigan
Daniel Forger: Robert W and Lynn H Browne Professor of Science, Professor of Mathematics, University of Michigan College of Literature, Science, and the Arts and Research Professor, Computational Medicine and Bioinformatics, University of Michigan Medical School
Jay Lee: Clark Distinguished Professor and Director of Industrial AI Center, University of Maryland
Venkat Raman: Professor of Aerospace Engineering and Mechanical Engineering, University of Michigan College of Engineering.

Event page, talk abstracts, and more details: https://midas.umich.edu/ai-in-science/ai-in-science-day-2023/

Visit the MIDAS Colloquia Series webpage (midas.umich.edu/colloquia-series/) for information about this series of events.

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Conference / Symposium Thu, 30 Mar 2023 15:28:50 -0400 2023-04-03T08:45:00-04:00 2023-04-03T17:00:00-04:00 Palmer Commons Michigan Institute for Data Science Conference / Symposium MIDAS AI in Science Day
CoderSpaces: Tuesdays Winter 2023 (April 4, 2023 9:30am) https://events.umich.edu/event/103187 103187-21806270@events.umich.edu Event Begins: Tuesday, April 4, 2023 9:30am
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:15:11 -0500 2023-04-04T09:30:00-04:00 2023-04-04T11:00:00-04:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces Winter 2023 - weekly data science hubs via Zoom
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.

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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
CoderSpaces: Wednesdays Winter 2023 (April 5, 2023 1:30pm) https://events.umich.edu/event/103188 103188-21806286@events.umich.edu Event Begins: Wednesday, April 5, 2023 1:30pm
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:18:31 -0500 2023-04-05T13:30:00-04:00 2023-04-05T15:00:00-04:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces - weekly data science hubs via Zoom
CoderSpaces: Tuesdays Winter 2023 (April 11, 2023 9:30am) https://events.umich.edu/event/103187 103187-21806271@events.umich.edu Event Begins: Tuesday, April 11, 2023 9:30am
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:15:11 -0500 2023-04-11T09:30:00-04:00 2023-04-11T11:00:00-04:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces Winter 2023 - weekly data science hubs via Zoom
CoderSpaces: Wednesdays Winter 2023 (April 12, 2023 1:30pm) https://events.umich.edu/event/103188 103188-21806287@events.umich.edu Event Begins: Wednesday, April 12, 2023 1:30pm
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:18:31 -0500 2023-04-12T13:30:00-04:00 2023-04-12T15:00:00-04:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces - weekly data science hubs via Zoom
"LHS Collaboratory / MIDAS Colloquium: "Implementing AI in Health" (April 17, 2023 8:00am) https://events.umich.edu/event/105462 105462-21811904@events.umich.edu Event Begins: Monday, April 17, 2023 8:00am
Location: Palmer Commons
Organized By: Department of Learning Health Sciences

LHS Collaboratory/MIDAS Colloquium co-presented by the Michigan Institute for Data Science

"Implementing AI in Health"

Monday, April 17, 20023
9:00 AM - 2:30 PM ET

In-person event
Palmer Commons, Great Lakes Room

100 Washtenaw Ave, Ann Arbor, MI 

Speakers:
Barbara A. Barry, PhD
Assistant Professor of Medicine | Collaborative Scientist
Robert D. & Patricia E. Kern Center for the Science of Healthcare Delivery, & Mayo Clinic Alix School of Medicine

Michael J. Kim, MD
Chief of Staff, National Artificial Intelligence Institute
U.S. Department of Veterans Affairs

Lisa S. Lehmann, PhD, MD
Associate Professor of Medicine
Center for Bioethics, Harvard Medical School

Michael Pencina, PhD
Vice Dean for Data Science and Director of Duke AI Health
Duke University School of Medicine

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Lecture / Discussion Sat, 15 Apr 2023 21:40:02 -0400 2023-04-17T08:00:00-04:00 2023-04-17T16:00:00-04:00 Palmer Commons Department of Learning Health Sciences Lecture / Discussion LHS Collaboratory logo
CoderSpaces: Tuesdays Winter 2023 (April 18, 2023 9:30am) https://events.umich.edu/event/103187 103187-21806272@events.umich.edu Event Begins: Tuesday, April 18, 2023 9:30am
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:15:11 -0500 2023-04-18T09:30:00-04:00 2023-04-18T11:00:00-04:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces Winter 2023 - weekly data science hubs via Zoom
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.

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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
CoderSpaces: Wednesdays Winter 2023 (April 19, 2023 1:30pm) https://events.umich.edu/event/103188 103188-21806288@events.umich.edu Event Begins: Wednesday, April 19, 2023 1:30pm
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:18:31 -0500 2023-04-19T13:30:00-04:00 2023-04-19T15:00:00-04:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces - weekly data science hubs via Zoom
CoderSpaces: Tuesdays Winter 2023 (April 25, 2023 9:30am) https://events.umich.edu/event/103187 103187-21806273@events.umich.edu Event Begins: Tuesday, April 25, 2023 9:30am
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:15:11 -0500 2023-04-25T09:30:00-04:00 2023-04-25T11:00:00-04:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces Winter 2023 - weekly data science hubs via Zoom
CoderSpaces: Wednesdays Winter 2023 (April 26, 2023 1:30pm) https://events.umich.edu/event/103188 103188-21806289@events.umich.edu Event Begins: Wednesday, April 26, 2023 1:30pm
Location: Off Campus Location
Organized By: Institute for Social Research

Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.

All members of the U-M community are invited to join our weekly virtual CoderSpaces to get research support and connect with others.

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Workshop / Seminar Tue, 10 Jan 2023 16:18:31 -0500 2023-04-26T13:30:00-04:00 2023-04-26T15:00:00-04:00 Off Campus Location Institute for Social Research Workshop / Seminar Coderspaces - weekly data science hubs via Zoom
MIDAS Seminar: Alfred Hero - NSF Priorities and Opportunities for Data Science and AI (June 1, 2023 1:00pm) https://events.umich.edu/event/107233 107233-21819157@events.umich.edu Event Begins: Thursday, June 1, 2023 1:00pm
Location: West Hall
Organized By: Michigan Institute for Data Science

Speaker: Dr. Alfred Hero, Program Director in the NSF CISE Directorate, and the John H. Holland Distinguished University Professor of Electrical Engineering and Computer Science and R. Jamison and Betty Williams Professor of Engineering, University of Michigan
Date: June 1, 2023
Time: 1:00-2:30 PM
Location: West Hall 340
Register here: https://myumi.ch/y2jAW

As data science and AI have continued to permeate society, the National Science Foundation (NSF) has introduced new programs in the foundations of the data sciences and its applications to scientific problems. This talk will provide an overview of some of NSF's activities and opportunities in data science and related fields.

Dr. Alfred Hero is the John H. Holland Distinguished University Professor of Electrical Engineering and Computer Science and the R. Jamison and Betty Williams Professor of Engineering at the University of Michigan, Ann Arbor. He is currently on leave from the University of Michigan as a Program Director in the CISE Directorate at the National Science Foundation. He is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) and the Society for Industrial and Applied Mathematics (SIAM). He is a recipient of the Fourier Award in Signal Processing from the IEEE.

Thirty minutes of networking with attendees following the presentation. Light refreshments provided.

Live-streaming is not available for this event. Post-event recording available upon request.

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Lecture / Discussion Thu, 25 May 2023 14:23:15 -0400 2023-06-01T13:00:00-04:00 2023-06-01T14:30:00-04:00 West Hall Michigan Institute for Data Science Lecture / Discussion MIDAS Seminar: Alfred Hero
LHS Collaboratory (June 21, 2023 3:00pm) https://events.umich.edu/event/108002 108002-21819440@events.umich.edu Event Begins: Wednesday, June 21, 2023 3:00pm
Location: Off Campus Location
Organized By: Department of Learning Health Sciences

Speaker:
Dipak Kalra, PhD, FRCGP, FACMI, FBCS
President, The European Institute for Innovation through Health Data
Professor of Health Informatics, UCL and Visiting Professor, University of Gant
One of the strongest drivers for Learning Health Systems in Europe right now is the urgency to strengthen health systems resilience through accelerated digital health transformation. This is a direct reaction to the struggles all of our health systems had during the COVID-19 pandemic.
Up to now digital health innovation has occurred in a rather piecemeal way, often through pilots that fail to scale up or be sustained. There is a real gap in the understanding of how digital health solutions, especially patient empowerment for disease self-management through smart technical solutions, can be appropriately targeted to the right patients, influence care pathways in an efficient and safe way, become culturally embraced by clinical teams and accountably adopted by healthcare provider organizations. There are several initiatives and opportunities in progress in Europe to accelerate the adoption of digital health technologies and to support the dissemination of good practices, which will be discussed during this talk.
In parallel, equally urgent, is the recognition that health data must be better used to support learning at scale, for example to be better prepared to gather intelligence rapidly as a lesson learned from the COVID-19 pandemic, and the need to accelerate research that can deliver innovative treatments, devices and algorithms. Many European countries have embarked upon establishing a national or regional health data infrastructure and ecosystem that enables the reuse of data for research. Most exciting of all, the European Commission has announced a multibillion program to establish a European Health Data Space (EHDS). An important success factor for this will be public trust, and therefore getting the governance model right for wide scale data reuse is critical. This talk will explain the approaches being taken across Europe to scale up the ability to analyze large volumes of health data, including its governance, and how the EHDS is anticipated to catalyze a step change in that scale of learning from health data.

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Lecture / Discussion Fri, 26 May 2023 00:22:13 -0400 2023-06-21T15:00:00-04:00 2023-06-21T16:30:00-04:00 Off Campus Location Department of Learning Health Sciences Lecture / Discussion LHS Collaboratory logo
The Design and Implementation of the Illinois Express Quantum Metropolitan Area Network (June 22, 2023 2:00pm) https://events.umich.edu/event/108778 108778-21820381@events.umich.edu Event Begins: Thursday, June 22, 2023 2:00pm
Location: Arbor Lakes
Organized By: Information and Technology Services (ITS)

Join Information and Technology Services (ITS) in welcoming Joaquin Chung to campus for a presentation on Quantum Networking, cutting-edge research, and one of the future technologies in campus network computing. This will be a very technical presentation geared for researchers and technologists.

Chung is a research scientist at the University of Chicago and Argonne National Laboratory who is working on the Illinois Express Quantum Metropolitan Area Network (IE QMAN). The IE QMAN is a functioning test bed that supports the transmission of quantum network traffic over existing dark fiber networks. This talk will describe details around the network control and physics involved in quantum data transmission.

Special Invitation:
Joaquin Chung will be available to chat with U-M researchers Thursday and Friday mornings during his time in Ann Arbor. If you would like to schedule a meeting with him, email T. Charles Yun (tcyun@umich.edu) to schedule an appointment.

Joaquin Chung is a postdoctoral appointee at the Data Science and Learning Division at Argonne National Laboratory. He received both his B.S. in Electronics and Communications Engineering (2007) and his M.Sc. in Communication Systems Engineering with Emphasis in Data Networks (2013) from University of Panama, Panama. He received his Ph.D in Electrical and Computer Engineering under the supervision of Dr. Henry Owen and Dr. Russ Clark at Georgia Institute of Technology, Atlanta, USA in December 2017. He is a Fulbright alumni, an IEEE member, and an ACM member. His research interests include software-defined networking, software-defined exchanges, cyber-infrastructure orchestration, edge computing, network security, and quantum communication networks.

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Lecture / Discussion Thu, 15 Jun 2023 16:50:23 -0400 2023-06-22T14:00:00-04:00 2023-06-22T15:00:00-04:00 Arbor Lakes Information and Technology Services (ITS) Lecture / Discussion Joaquin Chung, University of Chicago & Argonne National Laboratory
LHS Collaboratory (September 27, 2023 12:00pm) https://events.umich.edu/event/109037 109037-21820764@events.umich.edu Event Begins: Wednesday, September 27, 2023 12:00pm
Location: Palmer Commons
Organized By: Department of Learning Health Sciences

Theme: Putting Artificial Intelligence and Machine Learning into Practice

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Lecture / Discussion Sun, 09 Jul 2023 18:39:17 -0400 2023-09-27T12:00:00-04:00 2023-09-27T14:15:00-04:00 Palmer Commons Department of Learning Health Sciences Lecture / Discussion LHS Collaboratory logo
MPSDS JPSM Seminar Series - Everything You Need to Know When Utilizing Probability Panels: Best Practices in Planning, Fielding, and Analysis (September 27, 2023 12:00pm) https://events.umich.edu/event/112696 112696-21829462@events.umich.edu Event Begins: Wednesday, September 27, 2023 12:00pm
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

MPSDS SEMINAR SERIES
September 27, 2023
12:00 - 1:00 pm

IN PERSON AND VIA ZOOM
- In person, room 1070 Institute for Social Research.
- Via Zoom. The Zoom call will be locked 10 minutes after the start of the presentation.

EVERYTHING YOU NEED TO KNOW WHEN UTILIZING PROBABILITY PANELS: BEST PRACTICES IN PLANNING, FIELDING, AND ANALYSIS

Speakers: David Dutwin & Ipek Bilgen

Probability-based panel survey research is more widespread than ever, as the continuing decline in survey response rates makes cross-sectional sample surveys less and less accessible both in terms of fit for purpose data quality and cost. The attraction of probability panels for surveys is their ability to attain, dependent upon their recruiting methods, comparable response rates to cross-section polls, but at a lower cost and more expeditious execution. Panels are a unique type of survey research platform: Unlike cross-sections, panels recruit respondents specifically for future participation in surveys. In return, panelists are financially compensated, typically to join the panel in the first place, and then secondarily for each survey in which they participate.

These differences to cross-sectional surveys have a range of potential implications. How does the method and effort of recruiting impact who joins, and as a consequence what is best practice? What do panels do to retain panelists over time and which strategies are more successful than others? How much of a concern is panel conditioning, that is, the impact of persons repetitively taking surveys over time, and what are the implications for how frequently panelists should take surveys? How do panels, which exclusively request that panelists take surveys on the Internet, deal with people who do not have or are not comfortable using the Internet? What is the impact of panelist attrition and what are best efforts to replenish retired panelists? How successful are panels are executing true longitudinal surveys? And, given the additional layers of complexity, how are panel surveys properly weighted and estimated?

This seminar is meant to serve two purposes. First, it will serve as a guide for consumers of probability-based panels to understand what, in short, they are working with: What questions to ask and what features to understand about probability panels in evaluating their use for data collections, and how to best use probability-based panel data. Second, it will serve as an exploration of best practices for the practitioners of surveys: Raising issues of data quality, cost, and execution.

Learning Objectives:

1. For consumers of panel data: Understanding the features of panels with which to be knowledgeable; to know the important questions to ask panel vendors when assessing their fit for purpose of your research.
2. For researchers and practitioners: To understand the many dimensions and decision points in the building, maintenance, deployment, and delivery of multi-client panels and panel data.

Bios:

David Dutwin, PhD, is Senior Vice President for Strategic Initiatives, Business Ventures and Initiatives and Chief Scientist of AmeriSpeak at NORC at the University of Chicago. David provides scientific and programmatic thought leadership in support of NORC’s ongoing innovations. In addition to identifying new business opportunities, he lends expertise on research design conceptualization, methodological innovation, and product development. He leads the panel operations and the statistics and methods divisions of AmeriSpeak. David assists in NORC strategic vision and strategy, project acquisition and management of advance research methods. Prior research has focused on election methodology, surveying of low-incidence populations, the use of big data in survey research, and data quality in survey panels. He is a senior fellow of the Program for Opinion Research and Election Studies at the University of Pennsylvania. An avid member of the AAPOR community, David served as president from 2018-2019. He previously served on AAPOR’s Executive Council as conference chair and has served full terms on several committees. For over twenty years, he has taught courses in survey research and design, political polling, research methods, rhetorical theory, media effects, and other courses as an adjunct professor at the University of Pennsylvania, the University of Arizona, and West Chester University.

Ipek Bilgen, PhD, is a Principal Research Methodologist in the Methodology and Quantitative Social Sciences Department at NORC at the University of Chicago. Ipek is the Deputy Director of NORC’s Center for Panel Survey Sciences. Additionally, she oversees AmeriSpeak’s methodological research and innovations. As part of her role within AmeriSpeak, she also provides survey design expertise, questionnaire development and review support, and leads cognitive interview and usability testing efforts for client studies. Ipek received both her Ph.D. and M.S. from the Survey Research and Methodology (SRAM) Program at the University of Nebraska-Lincoln. She has published and co-authored articles in Journal of Official Statistics, Public Opinion Quarterly, Journal of Survey Statistics and Methodology, Survey Practice, Social Currents, Social Science Computer Review, Field Methods, Journal of Quantitative Methods, SAGE Research Methods, and Quality and Quantity on issues related to interviewing methodology, web surveys, online panels, internet sampling and recruitment approaches, nonresponse and measurement issues in surveys. In the past, she has served on AAPOR’s and MAPOR’s Executive Councils. Ipek is currently teaching at the Irving B. Harris Graduate School of Public Policy Studies at the University of Chicago and serving as Associate Editor of Public Opinion Quarterly (POQ).

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Lecture / Discussion Tue, 19 Sep 2023 15:29:30 -0400 2023-09-27T12:00:00-04:00 2023-09-27T13:00:00-04:00 Off Campus Location Michigan Program in Survey and Data Science Lecture / Discussion Flyer
Graduate Studies in Computational & Data Sciences Information Session (September 27, 2023 4:00pm) https://events.umich.edu/event/110296 110296-21824745@events.umich.edu Event Begins: Wednesday, September 27, 2023 4:00pm
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).

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Presentation Thu, 21 Sep 2023 10:24:54 -0400 2023-09-27T16:00:00-04:00 2023-09-27T17:00:00-04:00 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)
Michigan Genomics Initiative Symposium 2023 (September 29, 2023 10:00am) https://events.umich.edu/event/108642 108642-21820240@events.umich.edu Event Begins: Friday, September 29, 2023 10:00am
Location: Public Health I (Vaughan Building)
Organized By: Precision Health

The Michigan Genomics Initiative (MGI) Symposium is an annual event for faculty, researchers & students at U-M; a platform for fostering collaboration, sharing knowledge, and exploring the latest advancements in leveraging MGI data to improve human health.

Building upon the success of our previous symposiums, we’re implementing some new ideas too, including trainee lightning talks and collaboration pitches.

Please join us for our 3rd annual MGI Symposium!

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Conference / Symposium Thu, 10 Aug 2023 10:15:49 -0400 2023-09-29T10:00:00-04:00 2023-09-29T15:00:00-04:00 Public Health I (Vaughan Building) Precision Health Conference / Symposium Scan the QR code to learn more and/or register
Graduate Studies in Computational & Data Sciences Information Session (September 29, 2023 12:00pm) https://events.umich.edu/event/110296 110296-21824746@events.umich.edu Event Begins: Friday, September 29, 2023 12:00pm
Location: 1100 North University Building
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).

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Presentation Thu, 21 Sep 2023 10:24:54 -0400 2023-09-29T12:00:00-04:00 2023-09-29T13:00:00-04:00 1100 North University Building 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)
ICPSR Biennial Meeting: Next Gen ICPSR (October 4, 2023 9:00am) https://events.umich.edu/event/103800 103800-21807860@events.umich.edu Event Begins: Wednesday, October 4, 2023 9:00am
Location:
Organized By: Inter-university Consortium for Political and Social Research

We host this Biennial Meeting as part of the Consortium's collective mission to advance science. This event will support that mission via training and information-sharing in the areas of data curation and data management, research and classroom data resources, and data education opportunities to help data-driven individuals.

This event serves as an opportunity for researchers, teaching faculty, librarians, policymakers, students, data professionals, journalists, and more to virtually gather and share ideas that will aid us as a data community to deliver greater research impact.

There are no registration fees for this event.

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Conference / Symposium Sat, 21 Jan 2023 13:15:15 -0500 2023-10-04T09:00:00-04:00 2023-10-04T17:00:00-04:00 Inter-university Consortium for Political and Social Research Conference / Symposium ICPSR Biennial Meeting 2023 Save the Date
MPSDS JPSM Seminar Series - Using Partially Synthetic Frames to Evaluate Alternative Sample Designs for Estimating a Rare Business Characteristic (October 4, 2023 1:00pm) https://events.umich.edu/event/113114 113114-21830116@events.umich.edu Event Begins: Wednesday, October 4, 2023 1:00pm
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

MPSDS JPSM Seminar Series
October 4, 2023
12:00 - 1:00 pm EDT

In person, room 1070 Institute for Social Research, and via Zoom. The Zoom call will be locked 10 minutes after the start of the presentation.

Using Partially Synthetic Frames to Evaluate Alternative Sample Designs for Estimating a Rare Business Characteristic

Katherine Jenny Thompson, U.S. Census Bureau
Hang Joon Kim (University of Cincinnati)
Stephen Kaputa (U.S. Census Bureau)

In the “traditional'” finite population sampling framework, the sample designer has a complete list (frame) of eligible units with classification information and auxiliary variables related to surveyed characteristics. In our setting, the frame auxiliary variables are weakly related to the survey characteristic, which is not present for most units. Hence, using frame auxiliary variables to assess survey design efficacy can be misleading. Instead, we propose generating multiple partially synthetic frames, modeling characteristic values for each unit on the frame, then drawing repeated samples from each synthetic frame using the candidate sample design(s) to assess finite sample performance for each design within and between the synthetic frames. Focusing on establishment survey data, we illustrate our proposed approach on a subset of industries surveyed annually by the Business Enterprise Research and Development Survey.

Katherine Jenny Thompson is the Senior Mathematical Statistician in the Economic Directorate of the Census Bureau. Jenny holds a masters of science degree in Applied Statistics from the George Washington University and an bachelor or arts degree in Mathematics from Oberlin College. She is an American Statistical Association (ASA) Fellow, an elected member of the International Statistics Institute, and the Vice President Elect of the ASA. She is the Survey Statistics Editor-in-Chief of the Journal of Survey Statistics and Methodology and an Associate Editor for the Journal of Official Statistics. She has published papers on a variety of topics related to complex surveys in several journals, including the Journal of Official Statistics, Journal of the Royal Statistical Society (Series A), Survey Methodology, Annals of Applied Statistics, International Statistical Review, Journal of Survey Sampling and Methodology, and Public Opinion Quarterly.

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Lecture / Discussion Tue, 26 Sep 2023 13:43:03 -0400 2023-10-04T13:00:00-04:00 2023-10-04T14:00:00-04:00 Off Campus Location Michigan Program in Survey and Data Science Lecture / Discussion Flyer
ICPSR Biennial Meeting: Next Gen ICPSR (October 5, 2023 9:00am) https://events.umich.edu/event/103800 103800-21807861@events.umich.edu Event Begins: Thursday, October 5, 2023 9:00am
Location:
Organized By: Inter-university Consortium for Political and Social Research

We host this Biennial Meeting as part of the Consortium's collective mission to advance science. This event will support that mission via training and information-sharing in the areas of data curation and data management, research and classroom data resources, and data education opportunities to help data-driven individuals.

This event serves as an opportunity for researchers, teaching faculty, librarians, policymakers, students, data professionals, journalists, and more to virtually gather and share ideas that will aid us as a data community to deliver greater research impact.

There are no registration fees for this event.

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Conference / Symposium Sat, 21 Jan 2023 13:15:15 -0500 2023-10-05T09:00:00-04:00 2023-10-05T17:00:00-04:00 Inter-university Consortium for Political and Social Research Conference / Symposium ICPSR Biennial Meeting 2023 Save the Date
ICPSR Biennial Meeting: Next Gen ICPSR (October 6, 2023 9:00am) https://events.umich.edu/event/103800 103800-21807862@events.umich.edu Event Begins: Friday, October 6, 2023 9:00am
Location:
Organized By: Inter-university Consortium for Political and Social Research

We host this Biennial Meeting as part of the Consortium's collective mission to advance science. This event will support that mission via training and information-sharing in the areas of data curation and data management, research and classroom data resources, and data education opportunities to help data-driven individuals.

This event serves as an opportunity for researchers, teaching faculty, librarians, policymakers, students, data professionals, journalists, and more to virtually gather and share ideas that will aid us as a data community to deliver greater research impact.

There are no registration fees for this event.

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Conference / Symposium Sat, 21 Jan 2023 13:15:15 -0500 2023-10-06T09:00:00-04:00 2023-10-06T17:00:00-04:00 Inter-university Consortium for Political and Social Research Conference / Symposium ICPSR Biennial Meeting 2023 Save the Date
The Impact of AI on the Lives and Rights of Women in the US and the Middle East (October 10, 2023 12:00pm) https://events.umich.edu/event/113519 113519-21831110@events.umich.edu Event Begins: Tuesday, October 10, 2023 12:00pm
Location: Lane Hall
Organized By: Michigan Institute for Data Science

Overview: Artificial Intelligence (AI) is transforming every aspect of our society and our lives. However, just like any emerging technology, AI’s impact varies greatly for different demographic groups, in different geographic regions, and is shaped by social conventions, culture, religion, economic realities, among many other factors. We invite everyone who is interested in understanding the impact of AI to join Marina Alsahawneh and Merve Hickok for a discussion of the impact of AI on women in the US and the Middle East. They will discuss gender biases in AI algorithms, opportunities and gender inequity in the AI-enabled workforce, and cyber-based violence against women. They will discuss how these intersect with the political, social, cultural, economic and religious features of different geographic regions.

Speakers:
Marina Alsahawneh, Gender and Inclusion Officer at Jordan Open Source Association

Merve Hickok, Responsible Data & AI Advisor, Michigan Institute for Data Science

Moderator:
Jing Liu, Executive Director, Michigan Institute for Data Science

More information and registration here: https://midas.umich.edu/ai-womens-rights/

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Lecture / Discussion Wed, 04 Oct 2023 15:36:50 -0400 2023-10-10T12:00:00-04:00 2023-10-10T13:30:00-04:00 Lane Hall Michigan Institute for Data Science Lecture / Discussion AI-generated image of a woman in profile with abstract geometric designs
MPSDS JPSM Seminar Series - New data, new questions, old problems? Online behavioral data in social science research (October 11, 2023 12:00pm) https://events.umich.edu/event/113445 113445-21831024@events.umich.edu Event Begins: Wednesday, October 11, 2023 12:00pm
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

MPSDS JPSM Seminar Series
October 11, 2023
12:00 - 1:00 pm EDT

In person, room 1070 Institute for Social Research, and via Zoom. The Zoom call will be locked 10 minutes after the start of the presentation.

New data, new questions, old problems? Online behavioral data in social science research

Records of individuals’ online activities obtained from devices like personal computers and smartphones have received a lot of interest in the social sciences in recent years. Many have praised such data for allowing fine-grained observations of individuals’ online activities which would be impossible with more traditional data sources such as surveys. Recent work, however, warns that many data quality aspects of these novel data are so far poorly under- stood. As the number of observations can quickly reach several millions, researchers seem tempted to treat online behavioral data as gold standard, ignore what their data may be missing, and which other systematic biases may be present. In this talk, I present both applied and methodological work using online behavioral data in a typical social science setting. First, using within-between random effects models, I show how online behavioral data combined with a panel survey allows us to understand the effects of news media consumption from populist alternative news platforms on individuals’ political attitudes. Second, I show that online behavioral data, although containing detailed records of individuals’ social media use, are far from being complete. Using hidden Markov models, combined online behavioral data, survey records, and donated social media data, I show that the online behavioral data seem to completely fail in capturing social media use for about one third of the sample. I emphasize the need for researchers to navigate the complexities of online behavioral data, highlighting potentials and limitations.

Ruben Bach is a Research Fellow at the Mannheim Centre for European Social Research, University of Mannheim, Germany. His research is concerned with data quality in social science data products and applied computational social science (media consumption, political attitudes, socially responsible AI). In the fall of 2023, he is a visitor with the Department of Statistics and Actuarial Science, University of Waterloo, Ontario.

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Lecture / Discussion Tue, 10 Oct 2023 12:29:09 -0400 2023-10-11T12:00:00-04:00 2023-10-11T13:00:00-04:00 Off Campus Location Michigan Program in Survey and Data Science Lecture / Discussion Flyer
LHS Collaboratory (October 18, 2023 11:30am) https://events.umich.edu/event/112750 112750-21829504@events.umich.edu Event Begins: Wednesday, October 18, 2023 11:30am
Location: Palmer Commons
Organized By: Department of Learning Health Sciences

Speaker:
Ewout W. Steyerberg, PhD
Professor of Clinical Biostatistics & Medical Decision Making, Chair, Dept of Biomedical Data Sciences
Leiden University Medical Center, The Netherlands

Clinical prediction models aim to predict a person’s risk of an outcome (e.g. complications, mortality) given their observed characteristics (1). Risk predictions are traditionally derived from regression models. Artificial Intelligence, and specifically Machine Learning methods, are gaining interest to develop predictive algorithms. Predictions from classic models or AI algorithms need to be reliable to provide valid support for tasks such as shared decision making and whether a person should initiate a particular treatment.
The aim of this talk is to review recent developments in prediction model development and validation. Illustrations will be provided from different medical applications. Trustworthiness will be discussed in relation to the statistical aspects -such as sample size and the exceptionality of patients-, model uncertainty, and heterogeneity between contexts of practical application.

References
1. Steyerberg EW. Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating. 2nd ed. Springer International Publishing; 2019. (Statistics for Biology and Health). Available from: https://www.springer.com/gp/book/9783030163983

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Lecture / Discussion Tue, 19 Sep 2023 21:08:38 -0400 2023-10-18T11:30:00-04:00 2023-10-18T13:00:00-04:00 Palmer Commons Department of Learning Health Sciences Lecture / Discussion LHS Collaboratory logo
MPSDS JPSM Seminar Series - Implementing and Adjusting a Non-probability Web Survey: Experiences of EVENs (Survey on the Impact of COVID19 on Ethnic Minorities in the United Kingdom) (October 18, 2023 12:00pm) https://events.umich.edu/event/113847 113847-21831814@events.umich.edu Event Begins: Wednesday, October 18, 2023 12:00pm
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

MPSDS JPSM Seminar Series
October 11, 2023
12:00 - 1:00 pm EDT

In person, room 1070 Institute for Social Research and via Zoom.
The Zoom call will be locked 10 minutes after the start of the presentation.

Implementing and Adjusting a Non-probability Web Survey: Experiences of EVENs (Survey on the Impact of COVID19 on Ethnic Minorities in the United Kingdom)

Natalie Shlomo
Professor of Social Statistics, University of Manchester

This is joint work with Andrea Aparcio-Castro, Daniel Ellingworth, Angelo Moretti, Harry Taylor, Nissa Finney and James Nazroo

We discuss the challenges of implementing and adjusting a large-scale non-probability web survey. For the application, we focus on the 2021 Evidence for Equality National Survey (EVENS) which was led by the Centre on Dynamics of Ethnicity (CoDE) at the University of Manchester in the United Kingdom, in partnership with Ipsos-MORI. The aim was to understand the impact of the COVID19 pandemic on ethnic and religious minority groups in the UK. Standard probability-based surveys, even with ethnic minority group boosts, do not have the sample sizes required to obtain reliable estimates for small group statistics. We therefore designed a non-probability web survey of ethnic minority groups to overcome these limitations. We formed partnerships with community organizations and used innovative recruitment strategies, including digital and social media. Daily monitoring of the data collection against desired sample sizes and R-indicator calculations allowed the team to focus attention on the recruitment of specific groups in a responsive data collection mode. We also supplemented the sample with existing members in both established non-probability and probability-based panels in the UK. We describe the measures applied to improve the quality of the collected data and the statistical adjustments to correct for selection and coverage biases based on estimating the probability of participation in the non-probability sample using combined probability reference samples followed by calibration to auxiliary information from the UK Census 2021. We demonstrate how a pseudo-population bootstrap approach can be designed to obtain bootstrap weights to allow for statistical analyses and inference.

Natalie Shlomo is Professor of Social Statistics at the University of Manchester and publishes widely in the area of survey statistics, including small area estimation, adaptive survey designs, non-probability sampling, confidentiality and privacy, data linkage and integration. She has over 70 publications and refereed book chapters and a track record of generating external funding for her research. She is an elected member of the International Statistical Institute (ISI), a fellow of the Royal Statistical Society, a fellow of the Academy of Social Sciences and President 2023-2025 of the International Association of Survey Statisticians. She also serves on national and international Methodology Advisory Boards at National Statistical Institutes.

Homepage: https://www.research.manchester.ac.uk/portal/natalie.shlomo.html

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Lecture / Discussion Wed, 11 Oct 2023 14:15:21 -0400 2023-10-18T12:00:00-04:00 2023-10-18T13:00:00-04:00 Off Campus Location Michigan Program in Survey and Data Science Lecture / Discussion Flyer
MPSDS JPSM Seminar Series - Investigating the quality of digital trace and data donation (October 25, 2023 12:00pm) https://events.umich.edu/event/114041 114041-21832242@events.umich.edu Event Begins: Wednesday, October 25, 2023 12:00pm
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

MPSDS JPSM Seminar Series
October 25, 2023
12:00 - 1:00 pm EDT

In person, room 1070 Institute for Social Research, and via Zoom. The Zoom call will be locked 10 minutes after the start of the presentation.

Investigating the quality of digital trace and data donation

Challenges to traditional survey data collection such as increased costs and decreasing non-response are leading survey researchers to explore new forms of data. Recently, two types of data have received increased focus as a possible replacements or enhancements of surveys: digital trace data and data donation. Digital trace data refers to data produced while individuals interact with digital platforms, such as apps and websites. Data donation, on the other hand, refers to the acquisition of data from online platforms, such as Facebook or Google, directly from users. In a recent study we use an experimental design in a non-probability panel in Germany to explore non-response bias in data donated from Facebook as well measurement error in digital trace data from PCs and mobile phones.

Alexandru Cernat is an associate professor in the social statistics department at the University of Manchester. He has a PhD in survey methodology from the University of Essex and was a post-doc at the National Centre for Research Methods and the Cathie Marsh Institute. His research and teaching focus on: survey methodology, longitudinal data, measurement error, latent variable modelling, new forms of data and missing data. You can find out more about him and his research at: www.alexcernat.com

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Lecture / Discussion Mon, 16 Oct 2023 14:39:03 -0400 2023-10-25T12:00:00-04:00 2023-10-25T13:00:00-04:00 Off Campus Location Michigan Program in Survey and Data Science Lecture / Discussion Flyer
MPSDS JPSM Seminar Series - Flexible Formal Privacy for Public Data Curation (November 1, 2023 12:00pm) https://events.umich.edu/event/114344 114344-21832762@events.umich.edu Event Begins: Wednesday, November 1, 2023 12:00pm
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

MPSDS JPSM Seminar Series
November 1, 2023
12;00 - 1:00 pm EDT

In person, room 1070 Institute for Social Research, and via Zoom.
The Zoom call will be locked 10 minutes after the start of the presentation.

Flexible Formal Privacy for Public Data Curation

Researchers rely extensively on public datasets disseminated by official statistics agencies, universities, non-governmental organizations, and other data curators. With the increasing availability of data and computing power comes increased threats to privacy, as published statistics can more easily be used to reconstruct sensitive personal data. Formal privacy (FP) methods, like differential privacy (DP), provably limit such information leakage by injecting carefully chosen randomized noise into published statistics. However, the way DP accounts for privacy degradation requires this noise be injected into every statistic dependent on the confidential dataset. This fails to reflect data curator needs, social, legal or ethical requirements, and complex dependency structures between public and confidential datasets. In this talk, I'll discuss statistical methodology that addresses these problems. We propose a FP framework with novel characterizations of disclosure risk when assessing collections of statistics wherein only some statistics are published with DP guarantees. We demonstrate FP properties maintained by our proposed framework, propose data release mechanisms which satisfy our proposed definition, and prove the optimality properties of downstream statistical estimators based on these mechanism outputs. For this talk, I'll discuss a few end-to-end data analysis examples in public health and surveys, showing how theoretical trade-offs between privacy, utility, and computation time manifest in practice when assessing disclosure risks and statistical utility. I'll conclude with a discussion on the implications of this work for survey researchers, focusing on opportunities to incorporate privacy by design in survey planning, experimental design, and other data collection operations.

Jeremy Seeman is a Michigan Data Science Fellow at the Michigan Institute for Data Science (MIDAS) and MPSDS. He recently graduated with his PhD in statistics from Penn State University. Jeremy's research focuses on statistical data privacy, quantitative methods in the social sciences, and social values in data governance. He is the recipient of the U.S Census Bureau Dissertation Fellowship and the ASA Pride Scholarship. Prior to joining Penn State, Jeremy completed his BS in Physics and MS in Statistics at the University of Chicago, where he was a research fellow at the Center for Data Science and Public Policy.

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Lecture / Discussion Mon, 23 Oct 2023 14:35:41 -0400 2023-11-01T12:00:00-04:00 2023-11-01T13:00:00-04:00 Off Campus Location Michigan Program in Survey and Data Science Lecture / Discussion Flyer
MPSDS JPSM Seminar Series - 2020 California Neighborhoods Count: A validation of U.S. Census Population Counts and Housing Characteristic Estimates within California (November 8, 2023 12:00pm) https://events.umich.edu/event/114648 114648-21833254@events.umich.edu Event Begins: Wednesday, November 8, 2023 12:00pm
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

MPSDS JPSM Seminar Series
November 8, 2023
12:00 - 1:00 pm EST
The seminar will be locked 10 minutes after the start of the presentation.

2020 California Neighborhoods Count: A validation of U.S. Census Population Counts and Housing Characteristic Estimates within California

In response to long-standing concerns about the accuracy of census data and about a possible undercount, we conducted the California Neighborhoods Count (CNC) study — the first-ever independent, survey-based enumeration to directly evaluate the accuracy of the U.S. Census Bureau's population totals for a subset of California census blocks. This 2020 research was intended to produce parallel estimates of the 2020 Census population and housing unit totals at the census block level, employing the same survey items as the census and using enhanced data collection strategies and exploration of imputation methods. The CNC block-level population estimates were sensitive to the imputation method used to account for non-responding households, likely in part due to limited availability of administrative data to assist the imputations. CNC identified more housing units than Census (23,929 versus 22,668), which may be due to CNC’s in-person address canvassing. Despite advancements in geospatial imaging software, as well as many other approaches used by the U.S. Census Bureau to assess coverage and validate addresses, in-field address verification might yield a more complete accounting of inhabited housing units than partially conducting address canvassing with in-office approaches.

Lane Burgette is a Senior Statistician at the RAND Corporation. Dr. Burgette’s applied research is primarily focused on health policy, especially Medicare’s physician payment policies. Other recent research projects include an evaluation of the 2020 Census in California, gun policy research, and recidivism risk estimation for employer background checks. Dr. Burgette’s methodological research focuses on causal inference, methods for missing data, and Bayesian modeling. Prior to RAND, he earned his Ph.D. in Statistics at the University of Wisconsin, and was a post-doctoral researcher in the Department of Statistical Science at Duke University.

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Lecture / Discussion Mon, 30 Oct 2023 14:38:46 -0400 2023-11-08T12:00:00-05:00 2023-11-08T13:00:00-05:00 Off Campus Location Michigan Program in Survey and Data Science Lecture / Discussion Flyer
PSC Brownbag Series: Internship and Employment Opportunities at the US Census (November 20, 2023 12:00pm) https://events.umich.edu/event/111299 111299-21826636@events.umich.edu Event Begins: Monday, November 20, 2023 12:00pm
Location: Institute For Social Research
Organized By: Population Studies Center

The PSC Brown Bag Series runs live and on Zoom this year, Mondays from noon to 1.

Victoria Velkoff of the US Census Bureau presents at this brown bag presentation on internship and employment opportunities at the US Census.

Join us in person at ISR (Thompson Street) Room 1430.

Or online: Join Zoom Meeting
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Meeting ID: 954 1861 0585
Passcode: 818420
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Workshop / Seminar Thu, 31 Aug 2023 13:35:54 -0400 2023-11-20T12:00:00-05:00 2023-11-20T13:00:00-05:00 Institute For Social Research Population Studies Center Workshop / Seminar PSC Brownbag Series: Internship and Employment Opportunities at the US Census
LHS Collaboratory (November 21, 2023 12:00pm) https://events.umich.edu/event/114252 114252-21832563@events.umich.edu Event Begins: Tuesday, November 21, 2023 12:00pm
Location: Off Campus Location
Organized By: Department of Learning Health Sciences

“Learning Without Borders: AI's Dual Path in Veterans
and Global Health”
Speaker:
Akbar Waljee, MD, MSc, AGAF
Professor, Learning Health Sciences
Professor, Department of Internal Medicine, Gastroenterology & Hepatology

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Lecture / Discussion Thu, 19 Oct 2023 20:59:33 -0400 2023-11-21T12:00:00-05:00 2023-11-21T13:30:00-05:00 Off Campus Location Department of Learning Health Sciences Lecture / Discussion LHS Collaboratory logo
Using Arts Data from the Adolescent Brain Cognitive Development (ABCD) Study (November 30, 2023 12:00pm) https://events.umich.edu/event/114773 114773-21833590@events.umich.edu Event Begins: Thursday, November 30, 2023 12:00pm
Location: Off Campus Location
Organized By: Inter-university Consortium for Political and Social Research

Join us on November 30 at 12 pm (ET) to learn about the Adolescent Brain Cognitive Development (ABCD) study and how it is used to understand the arts' potential impacts on child health and brain development. During this webinar, Dr. Gay Dowling and Dr. John Iversen will provide an overview of the ABCD project and discuss how these data can be used to study connections between arts experiences and adolescent development. In addition, Dr. Iversen will highlight the arts-specific measures within ABCD, showing a high prevalence of the arts, with music being the most impactful activity among a wide range of artistic and athletic pursuits. This free webinar is hosted by NADAC, a data repository funded by the NEA. Register here: https://myumi.ch/2mAQp

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Presentation Wed, 01 Nov 2023 15:02:16 -0400 2023-11-30T12:00:00-05:00 2023-11-30T13:00:00-05:00 Off Campus Location Inter-university Consortium for Political and Social Research Presentation Webinar: Using Arts Data from the Adolescent Brain Cognitive Development (ABCD) Study
MPSDS JPSM Seminar Series - Using Synergies Between Survey Statistics and Causal Inference to Improve Transportability of Clinical Trials (January 17, 2024 12:00pm) https://events.umich.edu/event/108977 108977-21820671@events.umich.edu Event Begins: Wednesday, January 17, 2024 12:00pm
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

MPSDS Seminar Series
January 17, 2024
12:00 - 1:00 pm
In person, room 1070 Institute for Social Research, and via Zoom. The Zoom call will be locked 10 minutes after the start of the presentation.

Using Synergies Between Survey Statistics and Causal Inference to Improve Transportability of Clinical Trials

Medical researchers have understood for many years that treatment effect estimates obtained from a randomized clinical trial (RCT) -- termed efficacy'' -- can differ from those obtained in a general population -- termed effectiveness''. Only in the past decade has extensive work begun in the statistical literature to bridge this gap using formal quantitative methods. As noted by Rod Little in a letter to the editor in the New Yorker ...randomization in randomized clinical trials concerns the allocation of the treatment, not the selection of individuals for the study. The latter can have an important impact on the average size of a treatment effect,'' with RCT samples often designed, sometimes explicitly, to be more likely to include individuals for whom the treatment may be more effective.

This issue has been various termed generalizability'' or transportability." Why do we care about transportability? In RCTs we are in the happy situation were treatment assignment is randomized, so confounding due to either observed or unobserved (pre-treatment) covariates is not an issue. But while randomization of treatment eliminates the effect of unobserved confounders, at least net of non-compliance, it does not eliminate the effect of unobserved effect modifiers, which can impact the causal effect of treatment in a population that differs from the RCT sample population. The impact of these interactions on the marginal effect of treatment thus can differ between the RCT population and the final population of interest.

Concurrent with research into transportability has been research into making population inference from non-probability samples. There is a close overlap between these two approaches, particularly with respect to the non-probability inference methods that rely on information from a relevant probability sample of the target population to reduce selection bias effects. When there are relevant censuses or probability samples of the target patient population of interest, these methods can be adapted to transport information from the RCT to the patient population. Because the RCT setting focuses on causal inference, this adaptation involves extensions to estimate counterfactuals. Thus approaches that treat population inference as a missing data problem are a natural fit to connect these two strands of methodological innovation.

In particular, we propose to extend a pseudo-weighting'' methodology from other non-probability settings to a doubly robust'' estimator that treats sampling probabilities or weights as regression covariates to achieve consistent estimation of population quantities. We explore our proposed approach and compare with some standard existing methods in a simulation study to assess the effectiveness of the approach under differing degrees of selection bias and model misspecification, and compare it with results obtained using the RT data only and with existing methods that use inverse probability weights. We apply it to a study of pulmonary artery catheterization in critically ill patients where we believe differences between the trial sample and the larger population might impact overall estimates of treatment effects.

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Lecture / Discussion Mon, 03 Jul 2023 13:46:14 -0400 2024-01-17T12:00:00-05:00 2024-01-17T13:00:00-05:00 Off Campus Location Michigan Program in Survey and Data Science Lecture / Discussion Flyer
MPSDS JPSM Seminar Series - A Novel Methodology for Improving Applications of Modern Predictive Modeling Tools to Linked Data Sets Subject to Mismatch Error (January 24, 2024 12:00pm) https://events.umich.edu/event/116026 116026-21836083@events.umich.edu Event Begins: Wednesday, January 24, 2024 12:00pm
Location: Off Campus Location
Organized By: Michigan Program in Survey and Data Science

MPSDS JPSM Seminar Series
January 24, 2024
12:00 - 1:00 EST

In person, Room 1070, Institute for Social Research and via Zoom. The Zoom call will be locked 10 minutes after the start of the presentation.

A Novel Methodology for Improving Applications of Modern Predictive Modeling Tools to Linked Data Sets Subject to Mismatch Error

In recent years, the rise of social media platforms such as Twitter/X has provided social scientists with a wealth of user-content data, and there has been renewed interest in the utility of administrative records for increasing survey efficiency. Combining social media data, administrative records, and survey data has the potential to produce a comprehensive source of information for social research. These data are often collected from multiple sources and combined by probabilistic record linkage. For the analysis of these linked data files, advanced machine learning techniques, such as random forests, boosting, and related ensemble methods, have become essential tools for survey methodologists and data scientists. There is, however, a potential pitfall in the widespread application of these techniques to linked data sets that needs more attention. Linkage errors such as mismatch and missed-match errors can distort the true relationships between variables and adversely alter the performance metrics routinely output by predictive modeling techniques, such as variable importance, confusion matrices, RMSE, etc. Thus, the actual predictive performance of these machine-learning techniques may not be realized. In this presentation, I will describe a new general methodology designed to adjust modern predictive modeling techniques for the presence of mismatch errors in linked data sets. The proposed approach, based on mixture modeling, is general enough to accommodate various predictive modeling techniques in a unified fashion. I evaluate the performance of the new methodology with simulations implemented in R. I will conclude with recommendations for future work in this area.

Brady T. West is a Research Professor in the Survey Methodology Program, located within the Survey Research Center at the Institute for Social Research on the University of Michigan-Ann Arbor (U-M) campus. He earned his PhD from the Michigan Program in Survey and Data Science in 2011. Before that, he received an MA in Applied Statistics from the U-M Statistics Department in 2002, being recognized as an Outstanding First-year Applied Masters student, and a BS in Statistics with Highest Honors and Highest Distinction from the U-M Statistics Department in 2001. His current research interests include the implications of measurement error in auxiliary variables and survey paradata for survey estimation, selection bias in surveys, responsive/adaptive survey design, interviewer effects, and multilevel regression models for clustered and longitudinal data. He is the lead author of a book comparing different statistical software packages in terms of their mixed-effects modeling procedures (Linear Mixed Models: A Practical Guide using Statistical Software, Third Edition, Chapman Hall/CRC Press, 2022), and he is a co-author of a second book entitled Applied Survey Data Analysis (with Steven Heeringa and Pat Berglund), the second edition of which was published by CRC Press in June 2017. He was elected as a Fellow of the American Statistical Association in 2022.

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Lecture / Discussion Tue, 12 Dec 2023 16:19:25 -0500 2024-01-24T12:00:00-05:00 2024-01-24T13:00:00-05:00 Off Campus Location Michigan Program in Survey and Data Science Lecture / Discussion Flyer