Generalized Linear and Nonlinear Models for Correlated Data: Theory and Applications Using SAS
- List Price:
- Buy New: $69.26
as of 12/5/2013 15:00 EST details
- You Save: $20.69 (23%)
- Sales Rank:344,379
- Languages:English (Unknown), English (Original Language), English (Published)
- Media:Perfect Paperback
- Number Of Items:1
- Shipping Weight (lbs):2.7
- Dimensions (in):1.1 x 8.2 x 10.9
- Publication Date:September 24, 2012
Availability:Usually ships in 1-2 business days
- Used Book in Good Condition
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.
CERTAIN CONTENT THAT APPEARS ON THIS SITE COMES FROM AMAZON SERVICES LLC. THIS CONTENT IS PROVIDED ‘AS IS’ AND IS SUBJECT TO CHANGE OR REMOVAL AT ANY TIME.