Outcome-Assisted Multiple Imputation of Missing Treatments
利用结果信息辅助缺失处理状态的多重插补
We provide guidance on multiple imputation of missing at random treatments in observational studies. Specifically, analysts should account for both covariates and outcomes, i.e., not just use propensity scores, when imputing the missing treatments. To do so, we develop outcome-assisted multiple imputation of missing treatments: the analyst fits a regression for the outcome on the treatment indicator and covariates, which is used to sharpen the predictive probabilities for…