Generalized Estimating Equations [Hardcover]

James W. Hardin (Author), Joseph M. Hilbe (Author)

Book Description

Publication Date: July 30, 2002 | ISBN-10: 1584883073 | ISBN-13: 978-1584883074 | Edition: 1

Although powerful and flexible, the method of generalized linear models (GLM) is limited in its ability to accurately deal with longitudinal and clustered data. Developed specifically to accommodate these data types, the method of Generalized Estimating Equations (GEE) extends the GLM algorithm to accommodate the correlated data encountered in health research, social science, biology, and other related fields.

Generalized Estimating Equations provides the first complete treatment of GEE methodology in all of its variations. After introducing the subject and reviewing GLM, the authors examine the different varieties of generalized estimating equations and compare them with other methods, such as fixed and random effects models. The treatment then moves to residual analysis and goodness of fit, demonstrating many of the graphical and statistical techniques applicable to GEE analysis.

With its careful balance of origins, applications, relationships, and interpretation, this book offers a unique opportunity to gain a full understanding of GEE methods, from their foundations to their implementation. While equally valuable to theorists, it includes the mathematical and algorithmic detail researchers need to put GEE into practice.

Product Details

• Hardcover: 240 pages
• Publisher: Chapman and Hall/CRC; 1 edition (July 30, 2002)
• Language: English
• ISBN-10: 1584883073
• ISBN-13: 978-1584883074
• Product Dimensions: 9.2 x 6.4 x 0.4 inches
• Shipping Weight: 1 pounds (View shipping rates and policies)
• Average Customer Review: 5.0 out of 5 stars  See all reviews (2 customer reviews)
• Amazon Best Sellers Rank: #954,106 in Books (See Top 100 in Books)

Customer Reviews

Most Helpful Customer Reviews

27 of 27 people found the following review helpful:

5.0 out of 5 stars great book on a topic important to biostatisticians and containing details about computation, January 22, 2008

By 

Michael R. Chernick "statman31147" (Holland PA) - See all my reviews
(REAL NAME)   

This review is from: Generalized Estimating Equations (Hardcover)

GEE is an extension of the Generalized Linear Models that handles the correlation structure found in panel data and longitudinal or repeated measures analysis. The idea goes back to a paper by Zeger and Liang in 1986 and is well cover in their 1994 book with Diggle and its most recent revision. However, over the years the statistical packages have implemented GEE and variations of it in many different ways. This important new book not only provides a detailed description of GEE for theoreticians and practitioners but it also presents comparisons of how the various software products implement it. The packages include GLIM, SAS STAT/GENMOD, S-PLUS, Stata and RTI's product SUDAAN (designed specifically for survey data).
This book is well written and comprehensive and will make a great reference book. It even provides a chapter on model diagnostics. Many examples are illustrated using the various software packages.

As repeated measures or longitudinal data is very common in clinical trials this work is very imprtant and the text is a great reference for biostatisticians conducting clinical trials for pharmaceutical or medical device companies and for those in the medical research field that do such trials for research funding agencies.

4 of 4 people found the following review helpful:

5.0 out of 5 stars Excellent, clearly written, October 29, 2007

By 

Russell Barbour "skip" (New Haven CT.) - See all my reviews

Amazon Verified Purchase

This review is from: Generalized Estimating Equations (Hardcover)

I am just starting to apply GEE and this book is a must for getting a clear conceptual grasp of the subject and practical hands on demonstrations of how to apply it.