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Annette J. Dobson

An Introduction to Generalized Linear Models, Third Edition (Chapman & Hall/CRC Texts in Statistical Science) 3rd Edition

by Annette J. Dobson (Author), Adrian G. Barnett (Author)

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There is a newer edition of this item:

An Introduction to Generalized Linear Models (Chapman & Hall/CRC Texts in Statistical Science)
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Continuing to emphasize numerical and graphical methods, An Introduction to Generalized Linear Models, Third Edition provides a cohesive framework for statistical modeling. This new edition of a bestseller has been updated with Stata, R, and WinBUGS code as well as three new chapters on Bayesian analysis.

Like its predecessor, this edition presents the theoretical background of generalized linear models (GLMs) before focusing on methods for analyzing particular kinds of data. It covers normal, Poisson, and binomial distributions; linear regression models; classical estimation and model fitting methods; and frequentist methods of statistical inference. After forming this foundation, the authors explore multiple linear regression, analysis of variance (ANOVA), logistic regression, log-linear models, survival analysis, multilevel modeling, Bayesian models, and Markov chain Monte Carlo (MCMC) methods.

Using popular statistical software programs, this concise and accessible text illustrates practical approaches to estimation, model fitting, and model comparisons. It includes examples and exercises with complete data sets for nearly all the models covered.

ISBN-10

1584889500
ISBN-13

978-1584889502
Edition

3rd
Publisher

Chapman and Hall/CRC
Publication date

May 12, 2008
Language

English
Dimensions

6 x 0.75 x 9 inches
Print length

320 pages
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Annette J. Dobson
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Annette J. Dobson
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Trevor Hastie
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Paul S.P. Cowpertwait
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Editorial Reviews

Review

Overall, this new edition remains a highly useful and compact introduction to a large number of seemingly disparate regression models. Depending on the background of the audience, it will be suitable for upper-level undergraduate or beginning post-graduate courses.
―Christian Kleiber, Statistical Papers (2012) 53

The comments of Lang in his review of the second edition, that ‘This relatively short book gives a nice introductory overview of the theory underlying generalized linear modelling. …’ can equally be applied to the new edition. … three new chapters on Bayesian analysis are also added. … suitable for experienced professionals needing to refresh their knowledge … .
―Pharmaceutical Statistics, 2011

The chapters are short and concise, and the writing is clear … explanations are fundamentally sound and aimed well at an upper-level undergrad or early graduate student in a statistics-related field. This is a very worthwhile book: a good class text and a practical reference for applied statisticians.
―Biometrics

This book promises in its introductory section to provide a unifying framework for many statistical techniques. It accomplishes this goal easily. … Furthermore, the text covers important topics that are frequently overlooked in introductory courses, such as models for ordinal outcomes. … This book is an excellent resource, either as an introduction to or a reminder of the technical aspects of generalized linear models and provides a wealth of simple yet useful examples and data sets.
―Journal of Biopharmaceutical Statistics, Issue 2

Praise for the Second Edition:
The second edition … is successful in filling a void in the otherwise sparse literature on the subject of generalized linear models at the introductory level … a wide range of research applications are covered and ample workings are also provided to aid the reader in statistical calculations … I would highly recommend this text … .
―Kerrie Nelson, Statistics in Medicine, Vol. 23

Product details

Publisher ‏ : ‎ Chapman and Hall/CRC; 3rd edition (May 12, 2008)
Language ‏ : ‎ English
Paperback ‏ : ‎ 320 pages
ISBN-10 ‏ : ‎ 1584889500
ISBN-13 ‏ : ‎ 978-1584889502
Item Weight ‏ : ‎ 1.1 pounds
Dimensions ‏ : ‎ 6 x 0.75 x 9 inches

Best Sellers Rank: #2,096,920 in Books (See Top 100 in Books)
- #2,903 in Statistics (Books)
- #4,497 in Probability & Statistics (Books)

Customer Reviews:
34 ratings

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5 star		69%
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Eduardo Dávila

A book for several kinds of practitioners

Reviewed in the United States on May 25, 2010

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The book of Dobson and Barnett is an excellent tool for practitioners in Biostatistics, where They're dealing with non normal variables such as the ones associates to proportions, counts and positive data. The text is both theoric and applied, with several examples.
The third edition has been updated in Bayesian Analysis, which extends the book out of the frequentist perspective. Additionally, the text is presented for general use and applications because the use of R-package, a well known free software.

4 people found this helpful

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ram

This is a great book in GLMs

Reviewed in the United States on July 4, 2013

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Dobson does a very good job presenting material in a way that non-mathematicians can understand. There is some math but it is fairly basic linear algebra and it can be skimmed over without too much loss. Lots of good examples in R and BUGS.

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Total Bro

Probably one of the best and easiest stats books you'll ever read

Reviewed in the United States on October 18, 2016

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Probably one of the best and easiest stats books you'll ever read. The fact that there are some Chinese characters spread throughout the book in no way effects its readability.

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Milipede

Great overview of GLMs

Reviewed in the United States on February 8, 2011

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This book is a great overview for someone who already has taken a course in mathematical statistics with a strong focus on inference and estimation. However, don't expect too much detail on any of the methods. The real strength of this book is that fact that it is concise, and gives you the grand picture of GLMs in a very clear way. If you're looking for a book that goes into more detail but covers less material, I would highly suggest Freedman's Statistical Models: Theory and Practice.

2 people found this helpful

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wbman

This book gives a very satisfying treatment of generalized linear ...

Reviewed in the United States on December 30, 2015

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This book gives a very satisfying treatment of generalized linear models. Having studied things similar to this before, the way it introduces the fitting of the models and the exponential family of distributions is incredibly helpful in understanding why generalized linear models work the way they do. All in all, provides a solid foundation for further study of GLMs.

One person found this helpful

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sifc33

Solutions??

Reviewed in the United States on September 19, 2017

Verified Purchase

Pretty legit but anyone know where I can find the solutions for the problems at the end of each chapter?

One person found this helpful

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Public name

Great book for an introduction to GLM's

Reviewed in the United States on August 20, 2015

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Great book for an introduction to GLM's. Has some BUGS code for those who use (or want to learn) BUGS.

Reviewed in the United States on October 13, 2013

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This book explains the basics of Generalized Linear Model in a clear way. A special good recommendation for beginners in Statistics and an excellent reference for teachers.

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Top reviews from other countries

Evi

Very helpful

Reviewed in the United Kingdom on February 13, 2013

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This book was recommended for my university course in GLM. It explains everything in simple words and I found it very helpful.

Customer

Excellent summary of GLM

Reviewed in Germany on June 29, 2016

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While I love this book, I do not think this is a good introduction to complete beginners in the field. Knowledge of undergraduate level linear algebra and calculus are needed and the book is a bit technical. Having said this, I enjoyed reading it and recommend it to those who have the background in mathematics to read it.

Julia Bonn

Very good introduction to GLMs

Reviewed in Germany on December 16, 2014

Verified Purchase

Although this books requires some knowledge of calculus and algebra it is still readable for the non-mathematician. I really enjoyed reading this book as it builds up logically, has nice real-life examples and explains mathematical derivations when necessary. Can only recommend it.

Amazon Customer

Great book Easy to understand and follow

Reviewed in Canada on February 29, 2016

Verified Purchase

Great book Easy to understand and follow. I will recommend this book to anyone who want to learn GLM. THe delivery was fast too.

Alberto

satisfied

Reviewed in Italy on June 2, 2014

Verified Purchase

perfect intro to GLM. explains when you should use ANOVA, ANCOVA, MULTIPLE REGRESSION, GLM, CONTINGENCY TABLES, ...not too technical and full of examples. very fast-to-read

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An Introduction to Generalized Linear Models, Third Edition (Chapman & Hall/CRC Texts in Statistical Science) 3rd Edition

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