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An estimator of the survival function based on the semi-Markov model under dependent censorship.

作者信息

Lee Seung-Yeoun, Tsai Wei-Yann

机构信息

Department of Applied Mathematics, Sejong University, 98 Kunja-dong, Kwangjin-gu, Seoul, 143-747, Korea.

出版信息

Lifetime Data Anal. 2005 Jun;11(2):193-211. doi: 10.1007/s10985-004-0383-y.

DOI:10.1007/s10985-004-0383-y
PMID:15938546
Abstract

Lee and Wolfe (Biometrics vol. 54 pp. 1176-1178, 1998) proposed the two-stage sampling design for testing the assumption of independent censoring, which involves further follow-up of a subset of lost-to-follow-up censored subjects. They also proposed an adjusted estimator for the survivor function for a proportional hazards model under the dependent censoring model. In this paper, a new estimator for the survivor function is proposed for the semi-Markov model under the dependent censorship on the basis of the two-stage sampling data. The consistency and the asymptotic distribution of the proposed estimator are derived. The estimation procedure is illustrated with an example of lung cancer clinical trial and simulation results are reported of the mean squared errors of estimators under a proportional hazards and two different nonproportional hazards models.

摘要

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引用本文的文献

1
Estimating the survival function based on the semi-Markov model for dependent censoring.基于半马尔可夫模型对相依删失进行生存函数估计。
Lifetime Data Anal. 2016 Apr;22(2):161-90. doi: 10.1007/s10985-015-9325-0. Epub 2015 Mar 14.

本文引用的文献

1
A simple test for independent censoring under the proportional hazards model.比例风险模型下独立删失的一种简单检验。
Biometrics. 1998 Sep;54(3):1176-82.
2
A nonidentifiability aspect of the problem of competing risks.竞争风险问题的一个不可识别方面。
Proc Natl Acad Sci U S A. 1975 Jan;72(1):20-2. doi: 10.1073/pnas.72.1.20.