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Generalized Estimating Equations

October 16th, 2011 admin Leave a comment Go to comments

Book Features

  • Author: James W. Hardin
  • Language: English
  • ISBN10: 1584883073

Book Overview

>>>Even though potent and flexible, the approach of generalized linear models (GLM) is limited in its potential to accurately deal with longitudinal and clustered information. Developed specifically to accommodate these information kinds, the technique of Generalized Estimating Equations (GEE) extends the GLM algorithm to accommodate the correlated data encountered in health investigation, social science, biology, and other related fields.

Generalized Estimating Equations supplies the very 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 examine them with other methods, this kind of as fixed and random effects designs. The remedy then moves to residual analysis and goodness of match, demonstrating numerous of the graphical and statistical tactics applicable to GEE analysis.

With its cautious balance of origins, applications, relationships, and interpretation, this book provides a unique opportunity to obtain a complete understanding of GEE methods, from their foundations to their implementation. While equally useful to theorists, it consists of the mathematical and algorithmic detail researchers need to have to put GEE into practice….

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Categories: Medical Research

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  1. Michael R. Chernick “statman31147″
    October 16th, 2011 at 15:58 | #1
    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
    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…

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