Founded 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.

Classes are open for registration.
You do not have to be affiliated with the University to attend.
Registration and payment are required a minimum of two weeks prior to the start of the class.

July 7 and 9, 2026 (T/Th)
9:00am-1:00pm
Interventions in a Responsive Survey Design Framework
Presented by Brady T. West
Course Fee: $600

This course focuses on the implementation of potential interventions within a responsive survey design (RSD) framework. Many of these interventions have been tested experimentally, and the course will examine evaluations of those experiments to highlight their effectiveness. Emphasis will be placed on the role of experimental evaluation in the early early stages of RSD. This course will also cover practical methods for implementing interventions, including the design and execution of experiments to assess new approaches. In addition, strategies for applying these interventions in both interviewer-mediated and self-administered surveys (e.g., web and mail) will be discussed.

Brady T. West is a Research Professor in the Michigan Program in Survey and Data Science, 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 Methodology 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, adaptive and responsive 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 Chapman Hill in June 2017. He was elected as a Fellow of the American Statistical Association in 2022.