Identification and Inference on Treatment Effects under Covariate-Adaptive Randomization and Imperfect Compliance
协变量自适应随机化与不完全依从下处理效应的识别和推断
Randomized controlled trials (RCTs) frequently utilize covariate-adaptive randomization (CAR) (e.g., stratified block randomization) and commonly suffer from imperfect compliance. This paper studies the identification and inference for the average treatment effect (ATE) and the average treatment effect on the treated (ATT) in such RCTs with a binary treatment. We first develop characterizations of the identified sets for both estimands. Since data are generally not i.i.d.…