Authors:
- Generalized estimating equations have become increasingly popular in biometrical, econometrical, and psychometrical applications
- In this book, they are derived in a unified way using pseudo maximum likelihood estimation and the generalized method of moments
- References to the relevant literature discussing technical details are provided for the interested reader
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Statistics (LNS, volume 204)
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Table of contents (8 chapters)
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Front Matter
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Back Matter
About this book
Generalized estimating equations have become increasingly popular in biometrical, econometrical, and psychometrical applications because they overcome the classical assumptions of statistics, i.e. independence and normality, which are too restrictive for many problems.
Therefore, the main goal of this book is to give a systematic presentation of the original generalized estimating equations (GEE) and some of its further developments. Subsequently, the emphasis is put on the unification of various GEE approaches. This is done by the use of two different estimation techniques, the pseudo maximum likelihood (PML) method and the generalized method of moments (GMM).
The author details the statistical foundation of the GEE approach using more general estimation techniques. The book could therefore be used as basis for a course to graduate students in statistics, biostatistics, or econometrics, and will be useful to practitioners in the same fields.
Authors and Affiliations
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Institute for Medical Biometry and Statistics, University Hospital Schleswig-Holstein, University of Lübeck, Lübeck, Germany
Andreas Ziegler
About the author
Bibliographic Information
Book Title: Generalized Estimating Equations
Authors: Andreas Ziegler
Series Title: Lecture Notes in Statistics
DOI: https://doi.org/10.1007/978-1-4614-0499-6
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Science+Business Media, LLC 2011
Softcover ISBN: 978-1-4614-0498-9Published: 21 June 2011
eBook ISBN: 978-1-4614-0499-6Published: 17 June 2011
Series ISSN: 0930-0325
Series E-ISSN: 2197-7186
Edition Number: 1
Number of Pages: XV, 144
Topics: Statistical Theory and Methods