Richard Hahn

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!