Estimation/Imputation Strategies for Missing Data in Survival Analysis

We consider the problem of estimation from right-censored data, when the censoring indicator is possibly missing. We compare different estimatio/imputation strategies for recovering nuisance functional parameters. More precisely, we propose either a parametric strategy following a logistic model standard or a pure nonparametric regression strategy. We provide theoretical properties and numerical comparisons for these procedures.

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