Bayesian regression model for recurrent event data with event-varying covariate effects and event effect

DOI10.1080/02664763.2017.1367368OpenAlexW2750367953WikidataQ54984890 ScholiaQ54984890MaRDI QIDQ5035734

Li-An Lin, Sheng Luo, Barry R. Davis

Publication date: 22 February 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10161/15473

zbMATH Keywords

Markov chain Monte Carloheterogeneityfrailty modelsurvival modelevent dependence

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Uses Software

• SemiPar
• BayesDA

Cites Work

• Unnamed Item
• Unnamed Item
• The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
• Misspecifying the shape of a random effects distribution: why getting it wrong may not matter
• Cox's regression model for counting processes: A large sample study
• Recurrent events and the exploding Cox model
• Robustness of the linear mixed model to misspecified error distribution
• Modeling survival data: extending the Cox model
• Analysis of multivariate survival data
• Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
• The statistical analysis of recurrent events.
• A Frailty Model for Informative Censoring
• Shared parameter models under random effects misspecification
• On the regression analysis of multivariate failure time data
• Partial likelihood
• A Predictive Approach to Model Selection
• Bayesian Approach for Nonlinear Random Effects Models
• Semiparametric Regression
• Bayesian Measures of Model Complexity and Fit
• Semiparametric Regression for the Social Sciences
• A Joint Frailty Model for Survival and Gap Times Between Recurrent Events
• Deviance information criteria for missing data models