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用INLA进行贝叶斯生存分析

Danilo Alvares¹, Janet van Niekerk², Elias Teixeira Krainski²

¹MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.

Statistics in medicine

|June 26, 2024

概括

本教程展示了使用R包集成嵌套拉普拉斯近似法 (INLA) 拟合贝叶斯生存模型. 它涵盖了各种模型,为生存分析中的快速和准确的贝叶斯推理提供了语法示例.

科学领域:

生物统计学生物统计学
计算统计学计算统计学
生存分析的分析.

背景情况:

贝叶斯生存分析为建模时间到事件数据提供了一个灵活的框架.
传统的方法可能是计算密集型,特别是复杂的模型.
集成嵌套拉普拉斯近似 (INLA) 为贝叶斯推理提供了一个有效的替代方案.

研究的目的:

提供清晰的语法示例,以适应使用INLA的各种贝叶斯生存模型.
为了说明INLA和INLA联合R包用于生存数据分析的应用.
为纵向半连续标记,反复事件和终端事件展示一种新的联合模型.

主要方法:

使用集成嵌套拉普拉斯近似 (INLA) 进行近似贝叶斯推理.
通过INLA和INLA联合R包实施生存模型.
应用既有模型 (加速失效时间,比例危险,混合治愈,竞争风险,多状态,脆弱性) 和一个新的联合模型.

主要成果:

使用INLA演示了各种贝叶斯生存模型的实际实施.
为加速失效时间,比例危险,混合治愈,竞争性风险,多状态和脆弱性模型提供可重现的语法示例.
成功说明了复杂的纵向和生存数据场景的新联合模型.

结论:

INLA为贝叶斯生存分析提供了一个快速而准确的方法.
INLA和INLA联合R套餐促进了先进的生存模型的实施.
本教程是研究人员将贝叶斯方法应用于生存数据的实用指南.

关键词:

贝叶斯的推理贝叶斯的推理在这里,INLALA.在R-Packages中,使用的是R-Packages.联合建模联合建模时间到事件分析分析.

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