An Introduction to Generalized Linear Models (Quantitative Applications in the Social Sciences): 145

George Dunteman

ISBN 10: 0761920846 / ISBN 13: 9780761920847

Published by SAGE Publications, Inc, 2005

About this Item

Most items will be dispatched the same or the next working day. An apparently unread copy in perfect condition. Dust cover is intact with no nicks or tears. Spine has no signs of creasing. Pages are clean and not marred by notes or folds of any kind.

Seller Inventory # wbs8244083213

Bibliographic Details

• Title: An Introduction to Generalized Linear Models (Quantitative Applications in the Social Sciences): 145
• Publisher: SAGE Publications, Inc
• Publication Date: 2005
• Language: English
• ISBN 10: 0761920846
• ISBN 13: 9780761920847
• Binding: Soft cover
• Condition: Like New
• Weight: 158.8 grams

About this title

Synopsis

Do you have data that is not normally distributed and don′t know how to analyze it using generalized linear models (GLM)? Beginning with a discussion of fundamental statistical modeling concepts in a multiple regression framework, the authors extend these concepts to GLM and demonstrate the similarity of various regression models to GLM. Each procedure is illustrated using real life data sets. The book provides an accessible but thorough introduction to GLM, exponential family distribution, and maximum likelihood estimation; includes discussion on checking model adequacy and description on how to use SAS to fit GLM; and describes the connection between survival analysis and GLM. It is an ideal text for social science researchers who do not have a strong statistical background, but would like to learn more advanced techniques having taken an introductory course covering regression analysis.

About the Author

Prof. Ho′s research concerns with the development and application of quantitative methods in the neural and behavioral sciences. His current research interests include effective connectivity analysis in fMRI experiments, social network analysis, statistical approach for testing mathematical axioms, diagnostics in nonlinear SEM.