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Generalized Estimating Equations, Second Edition

Download or Read eBook Generalized Estimating Equations, Second Edition PDF written by James W. Hardin and published by CRC Press. This book was released on 2012-12-10 with total page 280 pages. Available in PDF, EPUB and Kindle.
Generalized Estimating Equations, Second Edition
Author :
Publisher : CRC Press
Total Pages : 280
Release :
ISBN-10 : 9781439881132
ISBN-13 : 1439881138
Rating : 4/5 (32 Downloads)

Book Synopsis Generalized Estimating Equations, Second Edition by : James W. Hardin

Book excerpt: Generalized Estimating Equations, Second Edition updates the best-selling previous edition, which has been the standard text on the subject since it was published a decade ago. Combining theory and application, the text provides readers with a comprehensive discussion of GEE and related models. Numerous examples are employed throughout the text, along with the software code used to create, run, and evaluate the models being examined. Stata is used as the primary software for running and displaying modeling output; associated R code is also given to allow R users to replicate Stata examples. Specific examples of SAS usage are provided in the final chapter as well as on the book’s website. This second edition incorporates comments and suggestions from a variety of sources, including the Statistics.com course on longitudinal and panel models taught by the authors. Other enhancements include an examination of GEE marginal effects; a more thorough presentation of hypothesis testing and diagnostics, covering competing hierarchical models; and a more detailed examination of previously discussed subjects. Along with doubling the number of end-of-chapter exercises, this edition expands discussion of various models associated with GEE, such as penalized GEE, cumulative and multinomial GEE, survey GEE, and quasi-least squares regression. It also offers a thoroughly new presentation of model selection procedures, including the introduction of an extension to the QIC measure that is applicable for choosing among working correlation structures. See Professor Hilbe discuss the book.


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