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.

chapter |4 pages

Introduction

chapter 1|34 pages

Classical likelihood theory

chapter 2|28 pages

Generalized linear models

chapter 3|32 pages

Quasi–likelihood

chapter 4|32 pages

Extended likelihood inferences

chapter 5|36 pages

Normal linear mixed models

chapter 6|30 pages

Hierarchical GLMS

chapter 7|26 pages

HGLMs with structured dispersion

chapter 8|36 pages

Correlated random effects for HGLMs

chapter 9|30 pages

Smoothing

chapter 10|24 pages

Double HGLMs

chapter 11|28 pages

Variable selection and sparsity models

chapter 12|26 pages

Multivariate and missing data analysis

chapter 13|14 pages

Multiple testing

chapter 14|26 pages

Random effect models for survival data