Introduction To General And Generalized Linear Models

Enables a clear comparison between general and generalized linear models; Provides an accessible description of advanced concepts of generalized linear models; Covers Gaussian-based hierarchical models and hierarchical generalized linear models; Introduces new concepts for mixed effects models that allow greater flexibility in model building and the data structures; Illustrates the power of the methods through many real-world examples, including drug development, pollutant emissions, and transportation safety; Uses R throughout to solve the examples; Offers solutions to the problems, additional exercises, a complete set of data for the examples, and a collection of lecture slides on the book’s website.