This tutorial shows how various Bayesian survival models can be fitted using the integrated nested Laplace approximation in a clear, legible, and comprehensible manner using the INLA and INLAjoint R-packages. Such models include accelerated failure time, proportional hazards, mixture cure, competing risks, multi-state, frailty, and joint models of longitudinal and survival data, originally presented in the article "Bayesian survival analysis with BUGS" (Alvares et al., 2021). In addition, we illustrate the implementation of a new joint model for a longitudinal semicontinuous marker, recurrent events, and a terminal event. Our proposal aims to provide the reader with syntax examples for implementing survival models using a fast and accurate approximate Bayesian inferential approach.

翻译：本教程展示了如何利用集成嵌套拉普拉斯近似方法，通过INLA和INLAjoint R软件包，以清晰、易读且易于理解的方式拟合多种贝叶斯生存模型。这些模型包括加速失效时间模型、比例风险模型、混合治愈模型、竞争风险模型、多状态模型、脆弱模型以及纵向和生存数据的联合模型，这些模型最初在文章《基于BUGS的贝叶斯生存分析》(Alvares等人，2021)中提出。此外，我们还展示了一种针对纵向半连续标记、复发事件和终止事件的新型联合模型的实现。本文旨在为读者提供使用快速且准确的近似贝叶斯推断方法实现生存模型的语法示例。