_:n299b451a1b6c48cf87e27db12d75df1fxb50
<http://schema.org/description>
"Survival analysis is one of the most important fields of statistics in\nmedicine and the biological sciences. In addition, the computational advances\nin the last decades have favoured the use of Bayesian methods in this context,\nproviding a flexible and powerful alternative to the traditional frequentist\napproach. The objective of this paper is to summarise some of the most popular\nBayesian survival models, such as accelerated failure time, proportional\nhazards, mixture cure, competing risks, frailty, and joint models of\nlongitudinal and survival data. Moreover, an implementation of each presented\nmodel is provided using a BUGS syntax that can be run with JAGS from the R\nprogramming language. Reference to other Bayesian R-packages are also\ndiscussed."
<https://api.deepai.org/profile/virgilio-gomez-rubio>