Compiled from the contributions of leading specialists, this book describes the tools and techniques for modelling the clustered data often encountered in medical, biological, environmental, and social science studies. It provides a comprehensive overview of marginal, condition, and random effects models using the likelihood, pseudo-likelihood, and generalized estimating equations methods. Focusing on binary data, the authors motivate and illustrate all aspects of these models in a variety of real applications, particularly developmental toxicity studies. They also discuss several variations and extensions. Clearly written, this treatment offers a practical, easily accessible survey of important modelling issues.
