Email this article 
Hide
Show all
| Authors: | Dimitris Rizopoulos | ||||
| Title: | The R Package JMbayes for Fitting Joint Models for Longitudinal and Time-to-Event Data Using MCMC | ||||
| Abstract: | Joint models for longitudinal and time-to-event data constitute an attractive modeling framework that has received a lot of interest in the recent years. This paper presents the capabilities of the R package JMbayes for fitting these models under a Bayesian approach using Markov chain Monte Carlo algorithms. JMbayes can fit a wide range of joint models, including among others joint models for continuous and categorical longitudinal responses, and provides several options for modeling the association structure between the two outcomes. In addition, this package can be used to derive dynamic predictions for both outcomes, and offers several tools to validate these predictions in terms of discrimination and calibration. All these features are illustrated using a real data example on patients with primary biliary cirrhosis. | ||||
|
Page views:: 6122. Submitted: 2014-05-10. Published: 2016-08-28. |
|||||
| Paper: |
The R Package JMbayes for Fitting Joint Models for Longitudinal and Time-to-Event Data Using MCMC
Download PDF
(Downloads: 5667)
|
||||
| Supplements: |
| ||||
| DOI: |
10.18637/jss.v072.i07
|
This work is licensed under the licenses Paper: Creative Commons Attribution 3.0 Unported License Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license. |