Generalized Linear and Nonlinear Models for Correlated Data: Theory and Applications Using SAS

Generalized Linear and Nonlinear Models for Correlated Data: Theory and Applications Using SAS

• Used Book in Good Condition

Edward F. Vonesh's <i>Generalized Linear and Nonlinear Models for Correlated Data: Theory and Applications Using SAS</i> 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.