Bayesian survival analysis with INLA
Fuente:
arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2022
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866910369422770176 |
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| author | Alvares, Danilo van Niekerk, Janet Krainski, Elias Teixeira Rue, Håvard Rustand, Denis |
| author_facet | Alvares, Danilo van Niekerk, Janet Krainski, Elias Teixeira Rue, Håvard Rustand, Denis |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2212_01900 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Bayesian survival analysis with INLA Alvares, Danilo van Niekerk, Janet Krainski, Elias Teixeira Rue, Håvard Rustand, Denis Methodology 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. |
| title | Bayesian survival analysis with INLA |
| topic | Methodology |
| url | https://arxiv.org/abs/2212.01900 |