Analysis of two-sample censored data using a semiparametric mixture model

被引：8
|
作者：
Li, Gang [1 ]
Lin, Chien-tai [2 ]
机构：
[1] Univ Calif Los Angeles, Dept Biostat, Los Angeles, CA 90095 USA
[2] Tamkang Univ, Dept Math, Tamsui 251, Taiwan
来源：
ACTA MATHEMATICAE APPLICATAE SINICA-ENGLISH SERIES | 2009年 / 25卷 / 03期
关键词：
Biased sampling; EM algorithm; maximum likelihood estimation; mixture model; semiparametric model; SELECTION BIAS MODELS; EMPIRICAL DISTRIBUTIONS; LIKELIHOOD; REGRESSION; VARIABLES;
D O I：
10.1007/s10255-008-8804-4
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
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.
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页码：389 / 398
页数：10
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