Sinopse

•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

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