Model-Assisted Complier Average Treatment Effect Estimates in Randomized Experiments with Noncompliance
不依从随机实验中依从者平均处理效应的模型辅助估计
Noncompliance is a common problem in randomized experiments in various fields. Under certain assumptions, the complier average treatment effect is identifiable and equal to the ratio of the intention-to-treat effects of the potential outcomes to that of the treatment received. To improve the estimation efficiency, we propose three model-assisted estimators for the complier average treatment effect in randomized experiments with a binary outcome. We study their asymptotic…