Friday, October 13, 2023
Wes Bonifay, Stanford University
Uncovering the Hidden Complexity of Statistical Models

Friday, November 3, 2023
Xinyuan Song, Chinese University of Hong Kong
Hidden Markov Models With An Unknown Number Of Hidden States

Friday, December 1, 2023
Irini Moustaki, London School of Economics and Political Science
Some New Developments On Pairwise Likelihood Estimation & Testing In Latent Variable Models

Friday, Feburary 24, 2023
Ben Domingue, Stanford University
Bookmaking for Binary Outcomes: Prediction, Profits, and the IMV

Friday, March 24, 2023
Joseph Schafer, United States Census Bureau
Modeling Coarsened Categorical Variables: Techniques and Software

Friday, April 7, 2023
Luke Miratrix, Harvard University
A Bayesian Nonparametric Approach to Geographic and 2-Dimensional Regression Discontinuity Designs

Friday, April 21, 2023
Matthias von Davier
Applications of Artificial Intelligence and Natural Language Processing in Educational Measurement

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

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"

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"

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"