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DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260603T130000
DTEND;TZID=America/Detroit:20260603T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903543@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
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DTSTAMP:20260603T060012
DTSTART;TZID=America/Detroit:20260603T130000
DTEND;TZID=America/Detroit:20260603T190000
SUMMARY:Other:Summer Recording Session\, June 3rd 1PM - 7PM
DESCRIPTION:Come join us for our weekly summer recording sessions! Absolutely no experience necessary\, just bring your passion for music and let us help you bring your ideas to life!\n \n(for example studio time can include: working on a pre-fleshed out plan on the digital audio workstation\, coming in with an instrument to record audio\, just having a ~vague~ idea in your head and wanting somewhere to put it\, humming a melody and letting us bring it to life\, chatting about music\, chatting about wolverine records\, just chatting in general\, etc- the sky is the limit!)
UID:148369-21904024@events.umich.edu
URL:https://events.umich.edu/event/148369
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:
LOCATION:Winberg Audio Studio - Shapiro Library
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20260603T072021
DTSTART;TZID=America/Detroit:20260603T131500
DTEND;TZID=America/Detroit:20260603T143000
SUMMARY:Workshop / Seminar:Center for Campus Involvement
DESCRIPTION:
UID:148302-21903827@events.umich.edu
URL:https://events.umich.edu/event/148302
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Sessions
LOCATION:Michigan Union
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20260519T101611
DTSTART;TZID=America/Detroit:20260603T140000
DTEND;TZID=America/Detroit:20260603T160000
SUMMARY:Lecture / Discussion:Design-Based Causal Inference for Clustered Randomized Experiments and Observational Studies
DESCRIPTION:Modern empirical research increasingly relies on comparative studies with complex designs\, including stratified and clustered treatment assignment\, multiple treatment arms\, and observational samples. These features arise naturally in education\, public health\, policy evaluation\, and many other fields\, but they also complicate causal estimation and inference by undermining the validity for familiar estimators and standard errors.\n\nThe first part of the dissertation studies clustered randomized trials with heterogeneous cluster sizes. We show that the commonly used estimators that average stratum-specific treatment-control contrasts can be inconsistent for the average treatment effect in such settings\, a problem that has received limited attention. We establish consistency of a simple alternative\, the Hájek estimator\, under standard asymptotic regimes\, develop an asymptotically conservative variance estimator valid under arbitrary stratum sizes\, and propose a score-type test with improved small- to moderate-sample performance.\n\nThe second part of the dissertation extends this framework to multi-arm stratified clustered experiments\, where inference must account for not only treatment-versus-control comparisons\, but also comparisons among active treatments. We show that regression adjustment admits a unified two-stage representation\, allowing adjustment models to be fit on the full sample\, a subset of units\, or external data. We establish multivariate asymptotic theory for vectors of covariate-adjusted Hájek estimators and develop a covariance matrix estimator that is asymptotically conservative in the positive semidefinite order.\n\nThe third part of the dissertation connects design-based inference for randomized experiments with matched and stratified observational studies. We compare the observational assignment mechanism to an emulated stratified clustered randomized trial with the same realized blocking structure. Assuming sufficient within-block homogeneity in treatment propensities\, we show that a sandwich-type variance estimator for the covariate-adjusted Hájek estimator is asymptotically conservative.\n\nTogether\, these results provide a unified design-based framework for estimation and inference in randomized and observational comparative studies. The dissertation contributes both diagnostic insight\, showing when common estimators fail\, and constructive methodology for valid causal inference in complex empirical designs.
UID:148339-21903956@events.umich.edu
URL:https://events.umich.edu/event/148339
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Dissertation
LOCATION:West Hall - 438
CONTACT:
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DTSTAMP:20260603T063048
DTSTART;TZID=America/Detroit:20260603T140000
DTEND;TZID=America/Detroit:20260603T150000
SUMMARY:Careers / Jobs:Resume Lab
DESCRIPTION:*RSVP required to attend. Click \"Join Event\" here: https://umich.joinhandshake.com/edu/events/1943778Just getting started building a resume? Have a draft but not sure how to make it better? Want to learn about resources available to revise your resume? Wherever you’re at Resume Lab is a great next step for you. Get real-time\, personalized support in a small group setting by checking out the Resume Lab.We will discuss and educate you on…- Design andformat- Writing a great bullet point- Targeting your resumefor specific internships/jobs If you're a Graduate Studentor Recent Grad\, please make a 1:1 appointment instead of attending the Lab because this event is designed for undergraduates. Note:This event's information is shown in Handshake as well as on the Happening @ Michigan calendar so that it will be seen by a larger number of U-M Students.#UCC
UID:147712-21901642@events.umich.edu
URL:https://events.umich.edu/event/147712
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:
LOCATION:
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