Asymptotically efficient estimation under semi-parametric random censorship models

Gerhard Dikta

Journal of Multivariate Analysis, 2014, vol. 124, issue C, 10-24

Abstract: We study the estimation of some linear functionals which are based on an unknown lifetime distribution. The observations are assumed to be generated under the semi-parametric random censorship model (SRCM), that is, a random censorship model where the conditional expectation of the censoring indicator given the observation belongs to a parametric family. Under this setup a semi-parametric estimator of the survival function was introduced by the author. If the parametric model assumption is correct, it is known that the estimated functional which is based on this semi-parametric estimator is asymptotically at least as efficient as the corresponding one which rests on the nonparametric Kaplan–Meier estimator.

Keywords: Survival analysis; Censored data; Semi-parametric random censorship model; Asymptotic efficiency (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (5)

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DOI: 10.1016/j.jmva.2013.10.002

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