Bayesian survival analysis with INLA

2022/12/04 by Alvares, Danilo, van Niekerk, Janet, Krainski, Elias Teixeira +2 · 2 citations
#FOS: Computer and information sciences #Methodology (stat.ME)

paper · doi:10.48550/arxiv.2212.01900

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.

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• A new approach for Bayesian joint modeling of longitudinal and cure-survival outcomes using the defective Gompertz distribution
• A Bayesian survival model induced by hurdle zero-modified power series discrete frailty with dispersion: an application in lung cancer

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