James G. Booth, James P. Hobert, Maximizing Generalized Linear Mixed Model Likelihoods with an Automated Monte Carlo EM Algorithm, Journal of the Royal Statistical Society. Series B (Statistical ...

Bayesian methods furnish an attractive approach to inference in generalized linear mixed models. In the absence of subjective prior information for the random-effect variance components, these ...

Linear mixed model (LMM) methodology is a powerful technology to analyze models containing both the fixed and random effects. The model was first proposed to estimate genetic parameters for ...