Analysis of Two-sample Censored Data Using a Semiparametric Mixture Model  

作　　者：Gang Li Chien-tai Lin 

机构地区：[1]Department of Biostatistics, University of California, Los Angeles, CA 90095, U.S.A. [2]Department of Mathematics, Tamkang University, Tamsui 251, Taiwan

出　　处：《Acta Mathematicae Applicatae Sinica》2009年第3期389-398,共10页应用数学学报（英文版）

基　　金：supported in part by the U.S.National Institute of Health(No.CA016042,No.P01AT003960);Chien-Tai Lin's research was supported in part by the National Science Council of Taiwan(No.89-2118-M-032-021,No.96-2628-M-032-002-MY3)

摘　　要：In this article we study a semiparametric mixture model for the two-sample problem with right censored data. The model implies that the densities for the continuous outcomes are related by a parametric tilt but otherwise unspecified. It provides a useful alternative to the Cox （1972） proportional hazards model for the comparison of treatments based on right censored survival data. We propose an iterative algorithm for the semiparametric maximum likelihood estimates of the parametric and nonparametric components of the model. The performance of the proposed method is studied using simulation. We illustrate our method in an application to melanoma.In this article we study a semiparametric mixture model for the two-sample problem with right censored data. The model implies that the densities for the continuous outcomes are related by a parametric tilt but otherwise unspecified. It provides a useful alternative to the Cox （1972） proportional hazards model for the comparison of treatments based on right censored survival data. We propose an iterative algorithm for the semiparametric maximum likelihood estimates of the parametric and nonparametric components of the model. The performance of the proposed method is studied using simulation. We illustrate our method in an application to melanoma.

关 键 词：Biased sampling EM algorithm maximum likelihood estimation mixture model semiparametric model 

分 类 号：O212.1[理学—概率论与数理统计] TV698.11[理学—数学]