Estimation for frailty measurement error Cox models based on profile likelihood and Bayes methods

被引：0

作者：

Zhang, Caiya ^{[1
]}

Gu, Xiaolu ^{[1
]}

Chen, Yingyu ^{[1
]}

机构：

[1] Zhejiang Univ City Coll, Dept Stat, Hangzhou, Peoples R China

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2021年 / 50卷 / 04期

关键词：

Cox model; Frailty; Measurement error; Profile likelihood; COVARIATE MEASUREMENT ERROR; PROPORTIONAL HAZARDS MODEL; SURVIVAL-DATA; REGRESSION; INFERENCE;

D O I：

10.1080/03610918.2019.1572763

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We study a class of frailty Cox models with measurement error in covariates for right censored clustered data. Based on the corrected profile likelihood and Bayes estimation, we construct estimators of the regression coefficients, baseline hazard and frailties in the models, which can reduce the dimension of estimated parameters and make the computation feasible. Numerical results show that frailty measurement error Cox model (FMCM) is more competitive and of good adaptivity than frailty Cox model (FCM) and measurement error Cox model (MCM) in terms of bias and mean square error.

引用

页码：1005 / 1018

页数：14

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