Random Effects in Censored Ordinal Regression: Latent Structure and Bayesian Approach

DOI10.1111/j.0006-341X.2000.00376.xzbMath1060.62683WikidataQ52076829 ScholiaQ52076829MaRDI QIDQ4667452

Douglas G. Simpson, Raymond J. Carroll, Min-ge Xie

Publication date: 20 April 2005

Published in: Biometrics (Search for Journal in Brave)

zbMATH Keywords

hierarchical modelrisk assessmentcensored responseGibbs sampler/Metropolis algorithm

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Censored data models (62N01) Bayesian inference (62F15)

Related Items (3)

The analysis of ordered categorical data: An overview and a survey of recent developments. (With discussion) ⋮ Modeling Clustered Ordered Categorical Data: A Survey ⋮ Asymptotics for generalized estimating equations with large cluster sizes

Cites Work

• Unnamed Item
• Unnamed Item
• Markov chains for exploring posterior distributions. (With discussion)
• Bayesian Methods for Censored Categorical Data
• Estimation in generalized linear models with random effects
• Maximum Likelihood Variance Components Estimation for Binary Data
• Maximum Likelihood Algorithms for Generalized Linear Mixed Models
• The Effect of Improper Priors on Gibbs Sampling in Hierarchical Linear Mixed Models
• Approximate Inference in Generalized Linear Mixed Models
• Informative Drop-Out in Longitudinal Data Analysis
• A note on the existence of the posterior distribution for a class of mixed models for binomial responses
• Bayesian Analysis of Binary and Polychotomous Response Data

This page was built for publication: Random Effects in Censored Ordinal Regression: Latent Structure and Bayesian Approach