Bayesian survival analysis with BUGS
Survival analysis is one of the most important fields of statistics in medicine and biological sciences. In addition, the computational advances in the last decades have favored the use of Bayesian methods in this context, providing a flexible and powerful alternative to the traditional frequentist...
| Autores principales: | , , , |
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| Formato: | Artículo preliminar |
| Lenguaje: | Inglés |
| Publicado: |
Wiley
2021
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| Materias: | |
| Acceso en línea: | http://hdl.handle.net/20.500.11939/7400 https://onlinelibrary.wiley.com/doi/full/10.1002/sim.8933 |
| _version_ | 1855492277688860672 |
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| author | Alvares, Danilo Lázaro, Elena Gómez-Rubio, Virgilio Armero, Carmen |
| author_browse | Alvares, Danilo Armero, Carmen Gómez-Rubio, Virgilio Lázaro, Elena |
| author_facet | Alvares, Danilo Lázaro, Elena Gómez-Rubio, Virgilio Armero, Carmen |
| author_sort | Alvares, Danilo |
| collection | ReDivia |
| description | Survival analysis is one of the most important fields of statistics in medicine and biological sciences. In addition, the computational advances in the last decades have favored the use of Bayesian methods in this context, providing a flexible and powerful alternative to the traditional frequentist approach. The objective of this article is to summarize some of the most popular Bayesian survival models, such as accelerated failure time, proportional hazards, mixture cure, competing risks, multi-state, frailty, and joint models of longitudinal and survival data. Moreover, an implementation of each presented model is provided using a BUGS syntax that can be run with JAGS from the R programming language. Reference to other Bayesian R-packages is also discussed. |
| format | Artículo preliminar |
| id | ReDivia7400 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | Wiley |
| publisherStr | Wiley |
| record_format | dspace |
| spelling | ReDivia74002025-04-25T14:48:19Z Bayesian survival analysis with BUGS Alvares, Danilo Lázaro, Elena Gómez-Rubio, Virgilio Armero, Carmen Bayesian inference, JAGS, R-packages, time-to-event analysis U10 Mathematical and statistical methods Survival analysis is one of the most important fields of statistics in medicine and biological sciences. In addition, the computational advances in the last decades have favored the use of Bayesian methods in this context, providing a flexible and powerful alternative to the traditional frequentist approach. The objective of this article is to summarize some of the most popular Bayesian survival models, such as accelerated failure time, proportional hazards, mixture cure, competing risks, multi-state, frailty, and joint models of longitudinal and survival data. Moreover, an implementation of each presented model is provided using a BUGS syntax that can be run with JAGS from the R programming language. Reference to other Bayesian R-packages is also discussed. 2021-06-02T12:13:08Z 2021-06-02T12:13:08Z 2021 acceptedVersion Alvares, D., Lazaro, E., Gomez‐Rubio, V. & Armero, C. (2021). Bayesian survival analysis with BUGS. Statistics in Medicine, 40(12), 2975-3020. 1097-0258 http://hdl.handle.net/20.500.11939/7400 10.1002/sim.8933 https://onlinelibrary.wiley.com/doi/full/10.1002/sim.8933 en Info:eu-repo/grantAgreement/ERDF//PPIC-2014-001-P Funding information: Consejería de Educación, Cultura y Deportes (JCCM, Spain) and FEDER, Grant Numbers: PPIC-2014-001-P and SBPLY/17/180501/000491; Ministerio de Ciencia e Innovación (MCI, Spain), Grant Number: PID2019-106341GB-I00 openAccess Wiley electronico |
| spellingShingle | Bayesian inference, JAGS, R-packages, time-to-event analysis U10 Mathematical and statistical methods Alvares, Danilo Lázaro, Elena Gómez-Rubio, Virgilio Armero, Carmen Bayesian survival analysis with BUGS |
| title | Bayesian survival analysis with BUGS |
| title_full | Bayesian survival analysis with BUGS |
| title_fullStr | Bayesian survival analysis with BUGS |
| title_full_unstemmed | Bayesian survival analysis with BUGS |
| title_short | Bayesian survival analysis with BUGS |
| title_sort | bayesian survival analysis with bugs |
| topic | Bayesian inference, JAGS, R-packages, time-to-event analysis U10 Mathematical and statistical methods |
| url | http://hdl.handle.net/20.500.11939/7400 https://onlinelibrary.wiley.com/doi/full/10.1002/sim.8933 |
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