Estimation of treatment effects with propensity score in the presence of
missing outcome data
 
   Lead Investigator:    Han Feng
   Institution      :    Renmin University of China
   E-Mail           :    hanfeng1661@163.com
   Proposal ID      :    252



   Proposal Description:
   In the analysis of observational data, missing outcome data often occur. Thus,    derivation of the average treatment effects estimators with missing outcome       data for causal inference is very important. We want to derive the asymptotic     variance based on the missing outcome data under the condition. We also want to verify the correctness of the asymptotic variance via simulation study.