Just Another Gibbs Sampling (JAGS) is a convenient tool to draw posterior samples using Markov Chain Monte Carlo for Bayesian modeling. However, the built-in function dinterval() to model censored data misspecifies the computation of deviance function, which may limit its usage to perform likelihood based model comparison. To establish an automatic approach to specify the correct deviance function in JAGS, we propose a simple alternative modeling strategy to implement Bayesian model selection for analysis of censored outcomes. The proposed approach is applicable to a broad spectrum of data types, which include survival data and many other right-, left- and interval-censored Bayesian model structures.
翻译:另一套Gibbs抽样(JAGS)是使用Markov链条蒙特卡洛(Markov Clain Monte Carlo)为贝耶斯人模型绘制后继样本的方便工具,然而,用于模拟受审查数据的内置函数隔热()显示偏差功能的计算方法,这可能会限制其用于进行基于可能性的模型比较。为了建立自动方法,指定JAGS的正确偏差功能,我们提出了一个简单的替代模式战略,以实施贝叶斯模式选择,用于分析受审查的结果。拟议方法适用于广泛的数据类型,其中包括生存数据和许多其他右、左和间审查的贝叶斯模式结构。