Bayesian survival analysis with INLA
Abstract
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.
Cite
@article{arxiv.2212.01900,
title = {Bayesian survival analysis with INLA},
author = {Danilo Alvares and Janet van Niekerk and Elias Teixeira Krainski and Håvard Rue and Denis Rustand},
journal= {arXiv preprint arXiv:2212.01900},
year = {2024}
}