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存在相依删失时标记生存数据的非参数估计。

Nonparametric estimation of marked survival data in the presence of dependent censoring.

机构信息

Janssen Research and Development, Spring House, Pennsylvania, USA.

Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

出版信息

Stat Med. 2023 May 30;42(12):1995-2008. doi: 10.1002/sim.9710. Epub 2023 Mar 21.

Abstract

We consider nonparametrically estimating the joint distribution of a survival time and mark variable, where the survival time is subject to right censoring and the mark variable is only observed when the survival time is not censored. The possibility of dependent censoring is allowed for using inverse probability of censoring weights. The proposed estimator is shown to be consistent and asymptotically normal. Finite sample behavior of the proposed methods are investigated via simulation study. Finally, we illustrate the nonparametric estimator from a recent HIV vaccine efficacy trial.

摘要

我们考虑非参数估计生存时间和标记变量的联合分布,其中生存时间受到右删失的影响,并且只有在生存时间未被删失时才观察到标记变量。使用逆概率删失权重允许存在相关删失的可能性。所提出的估计量被证明是一致的和渐近正态的。通过模拟研究研究了所提出方法的有限样本行为。最后,我们从最近的 HIV 疫苗功效试验中说明了非参数估计器。

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