Random effects in censored ordinal regression: latent structure and Bayesian approach |
| |
Authors: | Xie M Simpson D G Carroll R J |
| |
Institution: | Department of Statistics, Rutgers University, Piscataway, New Jersey 08855, USA. mxie@stat.rutgers.edu |
| |
Abstract: | This paper discusses random effects in censored ordinal regression and presents a Gibbs sampling approach to fit the regression model. A latent structure and its corresponding Bayesian formulation are introduced to effectively deal with heterogeneous and censored ordinal observations. This work is motivated by the need to analyze interval-censored ordinal data from multiple studies in toxicological risk assessment. Application of our methodology to the data offers further support to the conclusions developed earlier using GEE methods yet provides additional insight into the uncertainty levels of the risk estimates. |
| |
Keywords: | Censored response Gibbs sampler/Metropolis algorithm Hierarchical Model Risk assessment |
本文献已被 PubMed 等数据库收录! |