Dissertation Defense: Biqing Yang, Statistics PhD Candidate
Title: Bayesian Causal Inference with Gaussian Process Priors for Treatment Effect Estimation
Abstract: With the increasing demand for observational data analysis, developing robust statistical
methods to estimate causal effects has become increasingly important. We propose novel
Bayesian methods that integrate both propensity and prognostic scores with Gaussian process
priors to improve treatment effect estimation, particularly in scenarios where heterogeneous
treatment effect estimation is of interest.
We explore two primary approaches to leverage these techniques in causal inference. The first
approach develops a Bayesian semiparametric model that simultaneously incorporates
propensity and prognostic scores. By leveraging Gaussian process priors, we estimate both
the average treatment effect (ATE) and conditional average treatment effect (CATE) with
flexibility. We also establish theoretical properties, including asymptotic consistency and the
doubly robustness of the estimator, ensuring validity under a wide range of conditions. The
second approach addresses scenarios with no control group or an insufficient number of
control observations, extending Bayesian causal inference to external control data borrowing
by integrating Gaussian process priors with a propensity-score-integrated power prior. This
method enables more effective incorporation of external data while accounting for
heterogeneity in treatment effects. We illustrate its effectiveness through simulation studies and
an application to real-world data.
Both approaches are evaluated using extensive simulations and real-world applications,
showing improved performance compared to several existing methods. While many existing
methods focus solely on estimating the ATE, our findings contribute to a more comprehensive
Bayesian framework for causal inference, providing theoretical insights and practical guidelines
for estimating both the ATE and CATE.
Advisor: Xinyi Xu
Zoom Link: https://osu.zoom.us/j/97586739380?pwd=EbaxbTybo4LCQR4Ca0JivSbartNxd4.1