Generalized Linear Models: 37 Hardcover – Illustrated, 1 August 1989

by P. McCullagh (Author)

27

The success of the first edition of Generalized Linear Models led to the updated Second Edition, which continues to provide a definitive unified, treatment of methods for the analysis of diverse types of data. Today, it remains popular for its clarity, richness of content and direct relevance to agricultural, biological, health, engineering, and other applications.

The authors focus on examining the way a response variable depends on a combination of explanatory variables, treatment, and classification variables. They give particular emphasis to the important case where the dependence occurs through some unknown, linear combination of the explanatory variables.

The Second Edition includes topics added to the core of the first edition, including conditional and marginal likelihood methods, estimating equations, and models for dispersion effects and components of dispersion. The discussion of other topics-log-linear and related models, log odds-ratio regression models, multinomial response models, inverse linear and related models, quasi-likelihood functions, and model checking-was expanded and incorporates significant revisions.

Comprehension of the material requires simply a knowledge of matrix theory and the basic ideas of probability theory, but for the most part, the book is self-contained. Therefore, with its worked examples, plentiful exercises, and topics of direct use to researchers in many disciplines, Generalized Linear Models serves as ideal text, self-study guide, and reference.

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Print length

532 pages
Language

English
Publication date

1 August 1989
Dimensions

15.24 x 3.53 x 22.86 cm
ISBN-10

0412317605
ISBN-13

978-0412317606
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Product description

Review

"... an important, useful book, well-written by two authorities in the field..."
-Times Higher Education Supplement
"... an enormous range of work is covered... represents, perhaps, the most important field of research in theoretical and practical statistics. For all statisticians working in this field, the book is essential."
-Short Book Reviews
"... this is a rich book; rich in theory, rich in examples, and rich in a statistical sense. I highly recommend it."
-Biometrics
"... a definitive and unified presentation...by the outstanding experts of this field."
-Statistics
"This is a wonderful book... Reading the book is like listening to a good lecturer. The authors present the material clearly, and they treat the reader with respect. There is a balance between discussion, mathematical presentation of models, and examples."
-Technometrics

"... a complete introduction to the topic in a single monograph... a very readable book that provides the reader with great insight into a vast array of data analysis techniques...
-Siam Review

"... a unique and useful text for intermediate undergraduate teaching."
-THES

Review

"... an important, useful book, well-written by two authorities in the field..."
-Times Higher Education Supplement
"... an enormous range of work is covered... represents, perhaps, the most important field of research in theoretical and practical statistics. For all statisticians working in this field, the book is essential."
-Short Book Reviews
"... this is a rich book; rich in theory, rich in examples, and rich in a statistical sense. I highly recommend it."
-Biometrics
"... a definitive and unified presentation...by the outstanding experts of this field."
-Statistics
"This is a wonderful book... Reading the book is like listening to a good lecturer. The authors present the material clearly, and they treat the reader with respect. There is a balance between discussion, mathematical presentation of models, and examples."
-Technometrics

"... a complete introduction to the topic in a single monograph... a very readable book that provides the reader with great insight into a vast array of data analysis techniques...
-Siam Review

"... a unique and useful text for intermediate undergraduate teaching."
-THES

Product details

Publisher ‏ : ‎ Routledge; 2 edition (1 August 1989)
Language ‏ : ‎ English
Hardcover ‏ : ‎ 532 pages
ISBN-10 ‏ : ‎ 0412317605
ISBN-13 ‏ : ‎ 978-0412317606
Dimensions ‏ : ‎ 15.24 x 3.53 x 22.86 cm

Best Sellers Rank: 564,941 in Books (See Top 100 in Books)
- 1,283 in Probability & Statistics (Books)
- 512,342 in Textbooks & Study Guides

Customer Reviews:
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Amazon Customer

Excellent book on GLM for those who need to understand the math

Reviewed in the United States on 26 March 2014

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This was one of two books that were references for a course I took in Generalized Linear Models - GLM. This was an excellent book in explaining the technical (mathematical) details of the GLM, such as the importance of the link function (how covariates/predictors/explanatory variables are related to the response), the importance of moment generating functions and cumulant generating functions, and the contribution of various types of likelihoods (like conditional, quasi, and partial ) in parameter estimation in GLM. It also covers things like geometrical intepretations...which seems to be very important in the multivariate setting. Most of the problems in the book lean towards proofs. For example... problem 4.7 asks you to show that the ratio of a binomial and poisson random variable is asymptotically equivalent to a constant.

This book is kinda old, so things like Bayesian regression (which I'm not acquainted with...yet) or high dimensional data analysis are not going to be in this book. I know that the latest edition of Agresti's Categorical Data Analysis (CDA) does cover these topics though. Still, I think that the McCullagh book is more mathematically rigorous than Agresti's book, since it covers things like the geometrical interpretation of least squares estimation.

This book was clearly written for researchers who have a quantitative background - those who have a background in at least intermediate statistical theory (Casella & Berger) as well as statistical Linear Modeling. Anybody who only has some of this knowledge would probably find Agresti's Categorical Data Analysis more accessible (this was the other book used in our GLM course), and those don't have any math experience might find Agresti's An Introduction to Categorical Data Analysis a better book.

18 people found this helpful

Hy Tran

Well structured and easy to follow.

Reviewed in the United States on 29 March 2014

Verified Purchase

This book is very well structured and easy to follow. It provides both detail mathematical foundation of each topic and practical examples to showcase their usefulness in application.