Bayesian mixed model for survival data with semicompeting risks based on the Clayton copula

被引：0

作者：

Patino, Elizabeth Gonzalez ^{[1
]}

Tunes, Gisela ^{[2
]}

Tanaka, Nelson Ithiro ^{[2
]}

机构：

[1] Inst Butantan, Clin Trials & Pharmacovigilance Ctr, Sao Paulo, Brazil

[2] Univ Sao Paulo, Stat Dept, Sao Paulo, Brazil

来源：

BRAZILIAN JOURNAL OF PROBABILITY AND STATISTICS | 2024年 / 38卷 / 02期

关键词：

Semicompeting risks; Archimedean copulas; Clayton copula; data augumentation; chronic kidney disease; mixed model; SEMI-COMPETING RISKS; FRAILTY MODELS; DISTRIBUTIONS;

D O I：

10.1214/24-BJPS606

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：

Motivated by a chronic kidney disease dataset, we propose a Bayesian model for clustered semicompeting risks data based on Archimedean copulas, allowing for treatment switching. We consider the modeling of both independent and clustered observations. For clustered data, random effects are included to consider the dependence among observations in the same group. For the Clayton copula, we provide theoretical results for the posterior distribution when improper priors are used. A simulation study was conducted to evaluate the performance of the proposed model. Finally, the results of the analysis of chronic kidney disease data are discussed.

引用

页码：302 / 320

页数：19

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