Richard Hahn
Professor of statistics at Arizona State University focused on causal inference and regression tree models for social science and medical applications, with research interests in Bayesian foundations and heterogeneous treatment effects.
Best podcasts with Richard Hahn
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75 snips
Dec 27, 2025 • 1h 24min
Causal Inference & the "Bayesian-Frequentist War" | Richard Hahn S2E8 | CausalBanditsPodcast.com
In this enlightening discussion, Professor Richard Hahn from Arizona State University delves into the ongoing debate between Bayesians and frequentists in statistics. He shares insights on why Bayesian Additive Regression Trees (BART) are effective and how they compare to models like XGBoost. The conversation uncovers the significance of heterogeneous treatment effects and the challenges in generalizing RCT results. Richard emphasizes the importance of realistic simulation studies for understanding causal inference, while coining the term "feature-level selection bias"—a must-listen for stats enthusiasts!
15 snips
Jan 30, 2026 • 1h 8min
Do Heterogeneous Treatment Effects Exist? | Stephen Senn X Richard Hahn S2E9 | CausalBanditsPodcast
Stephen Senn, medical statistician focused on drug development and trials, and Richard Hahn, ASU statistics professor working on causal inference and regression trees, debate whether heterogeneous treatment effects are real and detectable. They discuss ethics of averaging, richer covariate measurement for discovery, machine learning on RCT data, trial design tradeoffs, and when subgroup findings become actionable.
