In the presence of informative right censoring and time-dependent covariates, we estimate the survival function in a fully nonparametric fashion. We introduce a novel method for incorporating multiple observations per subject when estimating the survival function at different covariate values and compare several competing methods via simulation. The proposed method is applied to survival data from people awaiting liver transplant.
Keywords: Kaplan–Meier estimation; Survival analysis; dependent censoring; inverse probability censoring weighting; organ transplantation.
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