Generalized Estimating Equations: 2nd Edition (e-Book) book cover

Generalized Estimating Equations

2nd Edition

By James W. Hardin, Joseph M. Hilbe

Chapman and Hall/CRC

277 pages

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pub: 2012-12-10
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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, al

Table of Contents

Introduction. Model Construction and Estimating Equations. Generalized Estimating Equations. Residuals, Diagnostics, and Testing. Programs and Datasets. References. Author Index. Subject Index.

About the Authors

James W. Hardin is the Division Director of Biostatistics and an associate professor in the Department of Epidemiology and Biostatistics at the University of South Carolina. He is also an affiliated faculty in the Institute for Families in Society. Professor Hardin was the initial author of Stata's xtgee command and has authored numerous articles and software applications related to GEE and associated models. Professor Hilbe and he have authored three editions of the popular Generalized Linear Models and Extensions and co-authored Stata's current glm command. He has also co-authored (with P. Good) four editions of the well-accepted Common Errors in Statistics (and How to Avoid Them).

Joseph M. Hilbe is a Solar System Ambassador with the Jet Propulsion Laboratory, an adjunct professor of statistics at Arizona State University, and an Emeritus Professor at the University of Hawaii. An elected fellow of the American Statistical Association and elected member of the International Statistical Institute (ISI), Professor Hilbe is president of the International Astrostatistics Association as well as chair of the ISI Sports Statistics and Astrostatistics committees. He has authored two editions of the bestseller Negative Binomial Regression, Logistic Regression Models, and Astrostatistical Challenges for the New Astronomy. He has also co-authored Methods of Statistical Model Estimation (with A. Robinson), Quasi-Least Squares Regression (with J. Shults), and R for Stata Users (with R. Muenchen).

Subject Categories

BISAC Subject Codes/Headings:
MATHEMATICS / Probability & Statistics / General