I had the second version of this book and it was the primary text for my Generalized Linear Model (GLM) course. I recently purchased the new version after reading about some of the differences between the two. I'll discuss my thoughts shortly.
First off, this book is another must have for those who will not only practice statistical modeling of categorical data, but who also need to be able understand the mathematical underpinnings of the GLM and the Generalized Linear Mixed Model (GLMM). Chapter 4, in particular, reviews the components of the GLM - systematic and random components, and the link function - and then goes on to explain what how these three differ depending on the type of your response ("y"): continuous data, binary data, count data, and so fourth. The next few chapters then go into detail on more of the application of the GLM for each of these type of data, followed by chapters discussing different models for GLMM - when your response variable is...Read more
I had the second version of this book and it was the primary text for my Generalized Linear Model (GLM) course. I recently purchased the new version after reading about some of the differences between the two. I'll discuss my thoughts shortly.First off, this book is another must have for those who will not only practice statistical modeling of categorical data, but who also need to be able understand the mathematical underpinnings of the GLM and the Generalized Linear Mixed Model (GLMM). Chapter 4, in particular, reviews the components of the GLM - systematic and random components, and the link function - and then goes on to explain what how these three differ depending on the type of your response ("y"): continuous data, binary data, count data, and so fourth. The next few chapters then go into detail on more of the application of the GLM for each of these type of data, followed by chapters discussing different models for GLMM - when your response variable is...Read more