An introduction to generalized linear models / Annette J. Dobson, Adrian G Barnett.

By: Dobson, Annette J, 1945-Contributor(s): Barnett, Adrian G Material type: Text

TextLanguage: English Series: Texts in statistical sciencePublication details: Boca Raton : CRC Press, c2008. Edition: 3rd edDescription: 307 p. : ill. ; 24 cmISBN: 9781584889502 (alk. paper); 1584889500 (alk. paper)Subject(s): Linear models (Statistics)DDC classification: 519.5 LOC classification: QA276 | .D589 2008Online resources: Table of contents only | WorldCat Details | E-book Fulltext

Contents:

TOC Model fitting -- Exponential family and generalized linear models -- Estimation -- Inference -- Normal linear models -- Binary variables and logistic regression -- Nominal and ordinal logistic regression -- Poisson regression and log-linear models -- Survival analysis -- Clustered and longitudinal data -- Bayesian analysis -- Markov chain Monte Carlo methods -- Example Bayesian analyses.

Summary: Summary: Offers a cohesive framework for statistical modeling. Emphasizing numerical and graphical methods, this work enables readers to understand the unifying structure that underpins GLMs. It discusses common concepts and principles of advanced GLMs, including nominal and ordinal regression, survival analysis, and longitudinal analysis.

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Item type	Current library	Collection	Call number	Copy number	Status	Barcode	Course reserves
E-Book	EWU Library E-book	Non-fiction	519.5 DOI 2008 (Browse shelf(Opens below))		Not For Loan
Text	EWU Library Reserve Section	Non-fiction	519.5 DOI 2008 (Browse shelf(Opens below))	C-1	Not For Loan	25696
Text	EWU Library Reserve Section	Non-fiction	519.5 DOI 2008 (Browse shelf(Opens below))	C-2	Not For Loan	25698
Text	EWU Library Circulation Section	Non-fiction	519.5 DOI 2008 (Browse shelf(Opens below))	C-3	Available	26760
Text	EWU Library Circulation Section	Non-fiction	519.5 DOI 2008 (Browse shelf(Opens below))	C-4	Available	26761	Introduction to Generalized Linear Models

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Includes bibliographical references (p. [295]-301) and index.

TOC Model fitting --
Exponential family and generalized linear models --
Estimation --
Inference --
Normal linear models --
Binary variables and logistic regression --
Nominal and ordinal logistic regression --
Poisson regression and log-linear models --
Survival analysis --
Clustered and longitudinal data --
Bayesian analysis --
Markov chain Monte Carlo methods --
Example Bayesian analyses.

Summary:
Offers a cohesive framework for statistical modeling. Emphasizing numerical and graphical methods, this work enables readers to understand the unifying structure that underpins GLMs. It discusses common concepts and principles of advanced GLMs, including nominal and ordinal regression, survival analysis, and longitudinal analysis.

Tahur Ahmed

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