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008 130619s2013 fluad sb 001 0 eng d
020 _a9781439881149 (ebook : PDF)
040 _aBD-DhSAU
_cBD-DhSAU
090 _aQA278.2
_b.H378 2013
092 _a519.544
_bH262
100 1 _aHardin, James W.
_q(James William)
245 1 0 _aGeneralized estimating equations
_h[electronic resource] /
_cJames W. Hardin, Joseph M. Hilbe.
250 _a2nd ed.
260 _aBoca Raton :
_bCRC Press,
_c2013.
300 _axv, 261 p. :
_bill.
504 _aIncludes bibliographical references and index.
505 0 _a1. Introduction -- 2. Model construction and estimating equations -- 3. Generalized estimating equations -- 4. Residuals, diagnostics, and testing -- 5. Programs and datasets.
520 _a"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"--
_cProvided by publisher.
520 _a"CHAPTER 1 Preface Second Edition We are pleased to offer this second edition to Generalized Estimating Equations. This edition benefits from comments and suggestions from various sources given to us during the past ten years since the first edition was published. As a consequence, we have enhanced the text with a number of additions, including more detailed discussions of previously presented topics, program code for examples in text, and examination of entirely new topics related to GEE and the estimation of clustered and longitudinal models. We have also expanded discussion of various models associated with GEE; penalized GEE, survey GEE, and quasi-least squares regression, as well as the number of exercises given at the end of each chapter. We have also added material on hypothesis testing and diagnostics, including discussion of competing hierarchical models. We have also introduced more examples, and expanded the presentation of examples utilizing R software. The text has grown by 40 pages. This edition also introduces alternative models for ordered categorical outcomes and illustrates model selection approaches for choosing among various candidate specifications. We have expanded our coverage of model selection criterion measures and introduce an extension of the QIC measure which is applicable for choosing among working correlation structures (see 5.1.2 in particular). This is currently a subject of considerable interest among statisticians having an interest in GEE"--
_cProvided by publisher.
530 _aAlso available in print edition.
538 _aMode of access: World Wide Web.
650 0 _aGeneralized estimating equations.
655 7 _aElectronic books.
_2lcsh
700 1 _aHilbe, Joseph.
776 1 _z9781439881132 (hardback)
856 4 0 _uhttp://marc.crcnetbase.com/isbn/9781439881149
_qapplication/PDF
999 _c11851
_d11850