معرفی
Thomas Leavitt is an Assistant Professor in the Department of Public Affairs at Baruch College's Marxe School of Public and International Affairs. His research bridges causal inference, Bayesian statistics, and design-based methodologies, with applications to racial/ethnic politics and comparative policy analysis in the U.S. and South Africa.
- Ph.D., Political Science, Columbia University
- M.Phil., Political Science, Columbia University
- M.A., Political Science, Columbia University
- M.A., Committee on International Relations, University of Chicago
- B.A., Political Science, DePauw University
His work focuses on developing robust statistical frameworks for causal analysis, including averaged prediction models for pre-post policy evaluation, sensitivity analysis for racial disparity studies, and randomization-based Bayesian inference. He investigates methodological challenges in audit experiments, observational studies, and proprietary data's impact on meta-analysis.
Recent publications include advancements in difference-in-differences methodology, causal mediation analysis, and algorithmic auditing techniques. His research integrates design-based rigor with Bayesian flexibility to address counterfactual assumptions and model uncertainty.
Leavitt leads courses in advanced quantitative methods, causal analysis, and data-driven policy evaluation at both graduate and undergraduate levels, emphasizing practical applications for public service.
