A Note on Bayesian Modeling Specification of Censored Data in JAGS

Abstract

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.

Integrating information and ecological practice: Two applications

“…Conditioned on the random effect α j(N EON ) , the likelihood for the NEON observations follows directly from the Beta probability density function. To derive the conditional likelihood for the NPS observations we rely on what practitioners sometimes call the "ones trick" (Qi et al (2020)).…”