Bayesian survival analysis with INLA

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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.” 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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Alvares, D., van Niekerk, J., Krainski, E. T., Rue, H., & Rustand, D. (2024). Bayesian survival analysis with INLA. Statistics in Medicine, 43(20), 3975–4010. https://doi.org/10.1002/sim.10160

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