Statistics Ph.D. Dissertation Defense - Angela Ting
Apr
7
2025

Apr
7
2025
Description
This 2025 Dissertation Defense will be held on Monday, April 7 from 3:00 p.m. to 5:00 p.m. with Angela Ting. This event will be hybrid. If you are able to attend in person, it will be held in WEL 5.204. If you need the Zoom link, please email stat.admin@austin.utexas.edu.
Title: Bayesian Nonparametric Methods for Heterogeneous Treatment and Mediation Effect Estimation
Advisor: Dr. Antonio Linero
Abstract: The causal inference literature has increasingly recognized that targeting treatment effect heterogeneity can lead to improved scientific understanding and policy recommendations. Similarly, studying the causal pathway connecting the treatment to the outcome can be useful as well. This dissertation develops Bayesian nonparametric methods for estimating heterogeneous causal mediation effects and treatment effects with complex outcomes. We introduce Bayesian Causal Mediation Forests (BCMF), a varying coefficient model based on Bayesian additive regression trees that estimates and carefully regularizes causal mediation effects. This framework is then extended to accommodate ordinal mediators, heteroskedastic variances, zero-inflated outcomes, and continuous treatments to enable more accurate modeling of real-world relationships. We also develop Bayesian nonparametric quasi-likelihood methods for estimating heterogeneous treatment effects with non-Gaussian outcomes, providing robust inference and reliable uncertainty quantification while relaxing restrictive distributional assumptions. The applicability of our proposed methods is demonstrated through comprehensive simulation studies and applications to real-world datasets, including the Medical Expenditures Panel Survey and RAND Health Insurance Experiment.
Location
This event will be hybrid. If you are able to attend in person, it will be held in WEL 5.204. If you need the Zoom link, please email stat.admin@austin.utexas.edu.
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