Product-limit Estimators and Cox Regression with Missing Censoring Information |
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Authors: | Ian W McKeague & Sundarraman Subramanian |
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Institution: | Florida State University,;University of Maine, Orono |
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Abstract: | The Kaplan–Meier estimator of a survival function requires that the censoring indicator is always observed. A method of survival function estimation is developed when the censoring indicators are missing completely at random (MCAR). The resulting estimator is a smooth functional of the Nelson–Aalen estimators of certain cumulative transition intensities. The asymptotic properties of this estimator are derived. A simulation study shows that the proposed estimator has greater efficiency than competing MCAR-based estimators. The approach is extended to the Cox model setting for the estimation of a conditional survival function given a covariate. |
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Keywords: | counting processes incomplete data Nelson–Aalen estimators product integral right censorship |
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