Generalized Estimating Equations

aw_product_id: 
34863971039
merchant_image_url: 
https://cdn.waterstones.com/bookjackets/large/9781/4398/9781439881132.jpg
merchant_category: 
Books
search_price: 
84.99
book_author_name: 
James W. Hardin
book_type: 
Hardback
publisher: 
Taylor & Francis Inc
published_date: 
10/12/2012
isbn: 
9781439881132
Merchant Product Cat path: 
Books > Science, Technology & Medicine > Mathematics & science > Mathematics > Probability & statistics
specifications: 
James W. Hardin|Hardback|Taylor & Francis Inc|10/12/2012
Merchant Product Id: 
9781439881132
Book Description: 
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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