A kernel-assisted imputation estimating method for the additive hazards model with missing censoring indicator

In this paper, a nonparametric imputation method is developed for the additive hazards model when the censoring indicator is missing at random (MAR). The asymptotic properties of the proposed estimator are derived and the performance of the proposed estimator is demonstrated by a numerical simulation.