Generalized linear models with random effects : unified analysis via h-likelihood

Description

This is the second edition of a monograph on generalized linear models with random effects that extends the classic work of McCullagh and Nelder. It has been thoroughly updated, with around 80 pages added, including new material on the extended likelihood approach that strengthens the theoretical basis of the methodology, new developments in variable selection and multiple testing, and new examples and applications. It includes an R package for all the methods and examples that supplement the book.-- Read more... Abstract: This is the second edition of a monograph on generalized linear models with random effects that extends the classic work of McCullagh and Nelder. It has been thoroughly updated, with around 80 pages added, including new material on the extended likelihood approach that strengthens the theoretical basis of the methodology, new developments in variable selection and multiple testing, and new examples and applications. It includes an R package for all the methods and examples that supplement the book Content: Classical likelihood theory -- Generalized linear models -- Quasi-likelihood -- Extended likelihood inferences -- Normal linear mixed models -- Hierarchical GLMS -- HGLMs with structured dispersion -- Correlated random effects for HGLMs -- Smoothing -- Double HGLMs -- Variable selection and sparsity models -- Multivariate and missing data analysis -- Multiple testing -- Random effect models for survival data.