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An estimator of the survival function based on the semi-Markov model under dependent censorship.
Lifetime Data Anal 2005; 11(2):193-211LD

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.

Authors+Show Affiliations

Department of Applied Mathematics, Sejong University, 98 Kunja-dong, Kwangjin-gu, Seoul, 143-747, Korea. leesy@sejong.ac.krNo affiliation info available

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

15938546

Citation

Lee, Seung-Yeoun, and Wei-Yann Tsai. "An Estimator of the Survival Function Based On the semi-Markov Model Under Dependent Censorship." Lifetime Data Analysis, vol. 11, no. 2, 2005, pp. 193-211.
Lee SY, Tsai WY. An estimator of the survival function based on the semi-Markov model under dependent censorship. Lifetime Data Anal. 2005;11(2):193-211.
Lee, S. Y., & Tsai, W. Y. (2005). An estimator of the survival function based on the semi-Markov model under dependent censorship. Lifetime Data Analysis, 11(2), pp. 193-211.
Lee SY, Tsai WY. An Estimator of the Survival Function Based On the semi-Markov Model Under Dependent Censorship. Lifetime Data Anal. 2005;11(2):193-211. PubMed PMID: 15938546.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - An estimator of the survival function based on the semi-Markov model under dependent censorship. AU - Lee,Seung-Yeoun, AU - Tsai,Wei-Yann, PY - 2005/6/9/pubmed PY - 2005/6/24/medline PY - 2005/6/9/entrez SP - 193 EP - 211 JF - Lifetime data analysis JO - Lifetime Data Anal VL - 11 IS - 2 N2 - 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. SN - 1380-7870 UR - https://www.unboundmedicine.com/medline/citation/15938546/An_estimator_of_the_survival_function_based_on_the_semi_Markov_model_under_dependent_censorship_ L2 - https://www.springerlink.com/openurl.asp?genre=article&issn=1380-7870&volume=11&issue=2&spage=193 DB - PRIME DP - Unbound Medicine ER -