Simultaneous inference for semiparametric mixed-effects joint models with skew distribution and covariate measurement error for longitudinal competing risks data analysis

被引：3

作者：

Lu, Tao ^{[1
]}

机构：

[1] Univ Nevada, Dept Math & Stat, 1664 Virginia St, Reno, NV 89557 USA

来源：

JOURNAL OF BIOPHARMACEUTICAL STATISTICS | 2017年 / 27卷 / 06期

关键词：

Bayesian inference; competing risks; longitudinal data; measurement error; partially linear mixed-effects models; proportional hazard models; skew distribution; survival data; BAYESIAN-APPROACH; T-DISTRIBUTION; SURVIVAL-DATA;

D O I：

10.1080/10543406.2017.1293080

中图分类号：

R9 [药学];

学科分类号：

1007 ;

摘要：

Semiparametric mixed-effects joint models are flexible for modeling complex longitudinal-competing risks data. Skew distributions are commonly observed for this type of data. Covariates in the joint models are usually measured with substantial errors. We propose a Bayesian method for semiparametric mixed-effects joint models with covariate measurement errors and skew distribution. The methods are illustrated with AIDS clinical data. Simulation results are conducted to validate the proposed methods.

引用

页码：1009 / 1027

页数：19

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