Simultaneous Bayesian modeling of longitudinal and survival data in breast cancer patients

被引：4

作者：

Azarbar, Ali ^{[1
]}

Wang, Yu ^{[2
]}

Nadarajah, Saralees ^{[2
]}

机构：

[1] Amirkabir Univ Technol, Dept Stat, Tehran, Iran

[2] Univ Manchester, Sch Math, Manchester, Lancs, England

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2021年 / 50卷 / 02期

关键词：

Longitudinal and survival data; MCMC method; Simultaneous Bayesian modeling; Time-to-event; TO-EVENT DATA; LIKELIHOOD APPROACH; JOINT MODEL; TIME; DISTRIBUTIONS; SYMMETRY; ERROR;

D O I：

10.1080/03610926.2019.1635701

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：

Using simultaneous Bayesian modeling, an attempt is made to analyze data on the size of lymphedema occurring in the arms of breast cancer patients after breast cancer surgery (as the longitudinal data) and the time interval for disease progression (as the time-to-event occurrence). A model based on a multivariate skew t distribution is shown to provide the best fit. This outcome was confirmed by simulation studies too.

引用

页码：400 / 414

页数：15

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