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   The R package jmbayes for fitting joint models for longitudinal and time-to-event data using MCMC  
   
نویسنده rizopoulos d.
منبع journal of statistical software - 2016 - دوره : 72 - شماره : 0
چکیده    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. © 2016,american statistical association. all rights reserved.
کلیدواژه Dynamic predictions; Mixed models; Random effects; Survival analysis; Time-varying covariates; Validation
آدرس erasmus medical center rotterdam,department of biostatistics,po box 2040,rotterdam,3000 ca, Netherlands
 
     
   
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