An Introduction to Generalized Linear Models, 3rd

Dobson, Annette J, and Barnett, Adrian G

ISBN 10: 1584889500 / ISBN 13: 9781584889502

Published by Chapman & Hall/CRC, Boca Raton, FL, 2008

About this Item

***INTERNATIONAL EDITION*** Read carefully before purchase: This book is the international edition in mint condition with the different ISBN and book cover design, the major content is printed in full English as same as the original North American edition. The book printed in black and white, generally send in twenty-four hours after the order confirmed. All shipments contain tracking numbers. Great professional textbook selling experience and expedite shipping service. Trade paperback (US). Glued binding. 307 p. Contains: Illustrations, black & white, Tables, black & white, Figures. Texts in Statistical Science (Chapman & Hall/CRC). Audience: General/trade.

Seller Inventory # K5820000995

Bibliographic Details

• Title: An Introduction to Generalized Linear Models, 3rd
• Publisher: Chapman & Hall/CRC, Boca Raton, FL
• Publication Date: 2008
• Language: English
• ISBN 10: 1584889500
• ISBN 13: 9781584889502
• Binding: Trade paperback
• Edition: 3rd ed. INTERNATIONAL EDITION
• Condition: New in new dust jacket.

About this title

Synopsis

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.

About the Author

Dobson, Department of Statistics and Centre for Clinical Epidemiology and Biostatistics, University of Newcastle, Australia.