Semiparametric regression analysis of failure time data with dependent interval censoring

被引:8
作者
Chen, Chyong-Mei [1 ]
Shen, Pao-sheng [2 ]
机构
[1] Natl Yang Ming Univ, Sch Med, Inst Publ Hlth, Taipei 11221, Taiwan
[2] Tunghai Univ, Dept Stat, Taichung 40704, Taiwan
关键词
dependent interval-censored data; frailty; recurrent event data; self-consistency algorithm; survival data; TRANSFORMATION MODELS; RECURRENT EVENTS; TERMINAL EVENT; SURVIVAL;
D O I
10.1002/sim.7361
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Interval-censored failure-time data arise when subjects are examined or observed periodically such that the failure time of interest is not examined exactly but only known to be bracketed between two adjacent observation times. The commonly used approaches assume that the examination times and the failure time are independent or conditionally independent given covariates. In many practical applications, patients who are already in poor health or have a weak immune system before treatment usually tend to visit physiciansmore often after treatment than those with better health or immune system. In this situation, the visiting rate is positively correlated with the risk of failure due to the health status, which results in dependent interval-censored data. While some measurable factors affecting health status such as age, gender, and physical symptom can be included in the covariates, some health-related latent variables cannot be observed or measured. To deal with dependent interval censoring involving unobserved latent variable, we characterize the visiting/examination process as recurrent event process and propose a joint frailty model to account for the association of the failure time and visiting process. A shared gamma frailty is incorporated into the Cox model and proportional intensity model for the failure time and visiting process, respectively, in a multiplicative way. We propose a semiparametric maximum likelihood approach for estimating model parameters and show the asymptotic properties, including consistency and weak convergence. Extensive simulation studies are conducted and a data set of bladder cancer is analyzed for illustrative purposes. Copyright (C) 2017 John Wiley & Sons, Ltd.
引用
收藏
页码:3398 / 3411
页数:14
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