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Edward F. 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.
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Nadine Gordimer
Paperback
 (2)
R391
R362
Discovery Miles 3 620
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