GENERALIZED LINEAR MIXED MODELS: MODERN CONCEPTS, METHODS AND APPLICATIONS (HB 2013) Hardcover

"Generalized Linear Mixed Models: Modern Concepts, Methods and Applications" introduces linear modeling through the comprehensive framework of the generalized linear mixed model (GLMM). For newcomers to linear models, it provides a broad understanding, connecting them to the wider statistics curriculum and highlighting key considerations for statistical modelers.   Beyond showcasing typical GLMM applications, the book presents the essential theory and methodology of linear models that handle random effects and non-normal data. Unlike traditional texts that emphasize normally distributed data, this book consistently uses the generalized mixed model approach, acknowledging that linear modeling data doesn't have to be normal and that effects can be fixed or random.   Featuring numerous examples using SAS® PROC GLIMMIX, this book is perfect for statistics graduate students, professionals looking to update their skills, and researchers new to the generalized linear model approach. It emphasizes data-driven methods and provides a foundation for expanding traditional linear model thinking to the realm of generalized linear mixed modeling.