Generalized Linear and Nonlinear Models for Correlated Data
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Generalized Linear and Nonlinear Models for Correlated Data

Theory and Applications Using SAS

Edward F. Vonesh

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  1. 552 pages
  2. English
  3. ePUB (mobile friendly)
  4. Only available on web
eBook - ePub
No longer available |Learn more

Generalized Linear and Nonlinear Models for Correlated Data

Theory and Applications Using SAS

Edward F. Vonesh

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About This Book

Edward Vonesh's Generalized Linear and Nonlinear Models for Correlated Data: Theory and Applications Using SAS is devoted to the analysis of correlated response data using SAS, with special emphasis on applications that require the use of generalized linear models or generalized nonlinear models. Written in a clear, easy-to-understand manner, it provides applied statisticians with the necessary theory, tools, and understanding to conduct complex analyses of continuous and/or discrete correlated data in a longitudinal or clustered data setting. Using numerous and complex examples, the book emphasizes real-world applications where the underlying model requires a nonlinear rather than linear formulation and compares and contrasts the various estimation techniques for both marginal and mixed-effects models. The SAS procedures MIXED, GENMOD, GLIMMIX, and NLMIXED as well as user-specified macros will be used extensively in these applications. In addition, the book provides detailed software code with most examples so that readers can begin applying the various techniques immediately.

This book is part of the SAS Press program.

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Information

Publisher
SAS Institute
Year
2014
ISBN
9781629592305

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