Joint modeling of failure time data with transformation model and longitudinal data when covariates are measured with errors

被引：0
作者：
Xi-ming Cheng
Qi Gong
机构：
[1] Beijing Information Science and Technology University,School of Applied Science
[2] Chinese Academy of Sciences,Academy of Mathematics and Systems Science
[3] University of Missouri,Department of Statistics
来源：
Acta Mathematicae Applicatae Sinica, English Series | 2012年 / 28卷
关键词：
EM algorithm; linear random effects model; maximum likelihood estimation; measurement error; 62G05; 62N01;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Semiparametric transformation models provide a class of flexible models for regression analysis of failure time data. Several authors have discussed them under different situations when covariates are timeindependent (Chen et al., 2002; Cheng et al., 1995; Fine et al., 1998). In this paper, we consider fitting these models to right-censored data when covariates are time-dependent longitudinal variables and, furthermore, may suffer measurement errors. For estimation, we investigate the maximum likelihood approach, and an EM algorithm is developed. Simulation results show that the proposed method is appropriate for practical application, and an illustrative example is provided.
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页码：663 / 672
页数：9
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