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Generalized Linear and Nonlinear Models for Correlated Data: Theory and Applications Using SAS
INR 8977
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Provides applied statisticians with the necessary theory, tools, and understanding to conduct complex analyses of continuous and/or discrete correlated data.
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- 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.
| Publisher | SAS Institute |
| Publication date | July 7, 2014 |
| Edition | Pap/Psc |
| Language | English |
| File size | 17.6 MB |
| Enhanced typesetting | Enabled |
| X-Ray | Not Enabled |
| Word Wise | Not Enabled |
| Print length | 554 pages |
| ISBN-10 | 9781612900919 |
| ISBN-13 | 978-1629592312 |
| Page Flip | Enabled |
| Item Weight | 2.5 lbs (1.13 kg) |
Product Description
Generalized Linear and Nonlinear Models for Correlated Data: Theory and Applications Using SAS
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INR 8977
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Features & Benefits
- Focuses on generalized linear and nonlinear models for correlated data.
- Written in a clear and easy-to-understand manner for applied statisticians.
- Covers complex analyses for continuous and discrete correlated data.
- Includes numerous real-world examples and applications.
- Extensively uses SAS procedures like MIXED, GENMOD, GLIMMIX, and NLMIXED.
- Provides detailed software code for immediate application of techniques.
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