Testing Effect Homogeneity and Confounding in High-Dimensional Experimental and Observational Studies
高维实验与观察性研究中的效应同质性及混杂检验
We propose a framework for testing the homogeneity of conditional average treatment effects (CATEs) across multiple experimental and observational studies. Our approach leverages multiple randomized trials to assess whether treatment effects vary with unobserved heterogeneity that differs across trials: if CATEs are homogeneous, this indicates the absence of interactions between treatment and unobservables in the mean effect. Comparing CATEs between experimental and…