●An introduction to quasi-likelihood methods that require weaker distributional assumptions, such as generalized estimating equation methods
●An overview of linear mixed models and generalized linear mixed models with random effects for clustered correlated data, Bayesian modeling, and extensions to handle problematic cases such as high dimensional problems
●Numerous examples that use R software for all text data analyses
●More than 400 exercises for readers to practice and extend the theory, methods, and data analysis
●A supplementary website with datasets for the examples and exercises

Alan Agresti
Distinguished Professor Emeritus
University of Forida
Gainesville, FL