ABSTRACT

Since their introduction in 1972, generalized linear models (GLMs) have proven useful in the generalization of classical normal models. Presenting methods for fitting GLMs with random effects to data, Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood explores a wide range of applications, including combining informati

chapter |4 pages

Introduction

chapter 1|32 pages

Classical likelihood theory

chapter 2|28 pages

Generalized Linear Models

chapter 3|32 pages

Quasi-likelihood

chapter 4|38 pages

Extended Likelihood Inferences

chapter 5|38 pages

Normal linear mixed models

chapter 6|30 pages

Hierarchical GLMs

chapter 7|28 pages

HGLMs with structured dispersion

chapter 8|36 pages

Correlated random effects for HGLMs

chapter 9|26 pages

Smoothing

chapter 10|26 pages

Random-effect models for survival data

chapter 11|24 pages

Double HGLMs

chapter 12|20 pages

Further topics