Description:

Department of Statistics Spring 2019 Seminar Series

Talk Title: Nonparametric Regression Models of Multilevel Treatment Effect Moderation

Speaker: Jared Murray, Assistant Professor of Statistics, University of Texas at Austin, Department of Information, Risk,and Operations Management and Department of Statistics and Data Science

Time: 11:00am

Abstract: Bayesian nonparametric approaches to causal inference have recently become popular. However, current approaches fail to address three important features in applications: Accounting for multilevel structure, allowing for targeted regularization, and providing interpretable summaries of scientifically meaningful quantities. We extend recently proposed BART-based methods to include all of these features. A key component of this model is a parameterization that allows treatment heterogeneity to be regularized separately from prognostic effects, and also parsimoniously incorporates multilevel structure. In an application to the National Study of Learning Mindsets (Yeager et. al., 2017) we use these new tools to provide meaningful insights about effect modification at the school and individual level. Our posterior summarization strategy avoids pitfalls common to existing approaches relying on post-hoc data snooping or large collections of hypothesis tests.

Location: Department of Statistics, Room B02, 2006 Sheridan Rd, Evanston 60208