Robust Estimation of Mean in Partially Linear Model With Missing Responses

To improve the robustness of an estimator, based on the covariate balancing propensity score and the augmented inverse probability weighted methods, a robust estimator of the population mean was obtained for the partially linear model, when the responses were missing at random. It is proved that the proposed estimator is asymptotically normal, and hence it can be applied to constructing the confidence region of the population mean.