Interdisciplinary Seminar Series

The Interdisciplinary Seminar Series on Statistical Methodology for Social and Behavioral Research aims to promote the connection between the statistics and social/behavioral science communities and to encourage more graduate students to participate in this area of interdisciplinary research.

This series is currently supported by the Department of Statistics and the Department of Educational Psychology at UConn, the Statistical and Applied Mathematical Sciences Institute (SAMSI) along with the New England Statistical Society (NESS).

For questions about this seminar series, please contact the organizers: Xiaojing Wang (statistics) and Betsy McCoach (educational psychology).

Fall 2022

Friday, September 9
Kosuke Imai, Harvard University
Experimental Evaluation of Algorithm-Assisted Human Decision-Making: Application to Pretrial Public Safety Assessment

Friday, October 7
Edsel A Pena, National Science Foundation
Searching for Truth through Data

Friday, November 11
Dylan S. Small, University of Pennsylvania
Testing an Elaborate Theory of a Causal Hypothesis

Past Events

Spring 2022

All events took place online.


Friday, January 8, 3 PM
Andrew Ho, Harvard University
"Test Validation for a Crisis: Five Practical Heuristics for the Best and Worst of Times"

Friday, March 4, 3 PM
Donald Hedeker, University of Chicago
"Shared Parameter Mixed-Effects Location Scale Models for Intensive Longitudinal Data"

Friday, March 25, 3 PM
Elizabeth Stuart, Johns Hopkins Bloomberg School of Public Health
"Combining Experimental and Population Data to Estimate Population Treatment Effects"

Friday, April 29
Luke Keele, University of Pennsylvania
"Approximate Balancing Weights for Clustered Observational Study Designs"

Fall 2021

All events took place online.


Friday, September 10, 12 PM
Susan Murphy, Harvard University
"Assessing Personalization in Digital Health"

Friday, October 1, 12 PM
Fan Li, Duke University
"Overlap Weighting for Causal Inference"

Friday, November 5, 12 PM
Jerry Reiter, Duke University
"How Auxiliary Information Can Help Your Missing Data Problem"

Friday, December 10, 12 PM
Jaime Lynn Speiser, Wake Forest University
"Machine Learning Prediction Modeling for Longitudinal Outcomes in Older Adults"

Spring 2021

All events took place online.


Friday, January 29, 12 PM
P. Richard Hahn, Arizona State University
"The Bayesian causal forest model: regularization, confounding, and heterogeneous effects"

Friday, February 26, 12 PM
Edward Ip, Wake Forest University
"Partially Ordered Responses and Applications"

Friday, March 26, 12 PM
David Dunson, Duke University
"Bayesian Pyramids: Identifying Interpretable Deep Structure Underlying High-dimensional Data"

Friday, April 16, 2 PM
Susan Paddock, NORC at the University of Chicago
"Causal Inference Under Interference in Dynamic Therapy Group Studies"

Friday, April 23, 2 PM
Jean-Paul Fox, University of Twente
"Bayesian Covariance Structure Modeling: An Overview and New Developments"

Friday, April 30, 12 PM
Jennifer Hill, Columbia University
"thinkCausal: One Stop Shopping for Answering your Causal Inference Questions"

Friday, May 21, 12 PM
David Kaplan, University of Wisconsin – Madison
"Developments and Extensions in the Quantification of Model Uncertainty: A Bayesian Perspective"

Friday, June 18, 12 PM
Jon Krosnick, Stanford University
"The Collapse of Scientific Standards in the World of High Visibility Survey Research"

Fall 2020

All events took place online.


Friday, November 20, 11:30 AM
Bengt Muthen, University of California
"Recent Advances in Latent Variable Modeling"

Friday, December 18, 12 PM
Paul De Boeck, The Ohio State University
"Response Accuracy and Response Time in Cognitive Tests"