Generalized Linear and Nonlinear Models for Correlated Data Book Reviews
Generalized Linear and Nonlinear Models for Correlated Data by Edward F. Vonesh Book Summary
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.
Book Name | Generalized Linear and Nonlinear Models for Correlated Data |
Genre | Mathematics |
Author | Edward F. Vonesh |
Published | 07 July 2014, Monday |
Language | English |
E-Book Size | 18 MB |
Generalized Linear and Nonlinear Models for Correlated Data (Edward F. Vonesh) Book Reviews 2024
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Summary of Generalized Linear and Nonlinear Models for Correlated Data by Edward F. Vonesh
The Generalized Linear and Nonlinear Models for Correlated Data book written by Edward F. Vonesh was published on 07 July 2014, Monday in the Mathematics category. A total of 40 readers of the book gave the book 0 points out of 5.
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