My biostatistics collaborator is speaking this Tues 21 Oct, 11am at the NYU Department of Population Health, room CR 314 and on zoom:

Generalizing Treatment Effects from Trials to EHR Populations using Propensity Score Predictive Inference

Although randomized controlled trials provide strong internal validity, they often lack external validity when generalized to populations. This limitation, known as generalizability, arises when trial participants are not representative of the target population. To address this, we develop an interaction-based Propensity Score Predictive Inference (PSPI) method that leverages propensity scores for trial participation combined with flexible outcome models. We introduce two robust PSPI variants that estimate potential outcomes across treatment groups by incorporating natural cubic splines of the propensity score and modeling high-dimensional covariates with Bayesian Additive Regression Trees.

Generalization is important!