Am J Epidemiol 2003; 157:364-375.
Copyright © 2003 by Johns
Hopkins Bloomberg School of Public Health
PRACTICE OF EPIDEMIOLOGY |
Statistical Analysis of Correlated Data Using Generalized Estimating Equations: An Orientation
1 Department of Epidemiology and Biostatistics, Faculty of Medicine, McGill University, Montreal, Quebec, Canada.
2 Division of Clinical Epidemiology, Royal Victoria Hospital, Montreal, Quebec, Canada.
3 Division of Epidemiology and Biostatistics, Department of Epidemiology and Social Medicine, Albert Einstein College of Medicine of Yeshiva University, Bronx, NY.
4 Department of Family Medicine and Community Health, School of Medicine, Tufts University, Boston, MA.
The method of generalized estimating equations (GEE) is often used to analyze longitudinal and other correlated response data, particularly if responses are binary. However, few descriptions of the method are accessible to epidemiologists. In this paper, the authors use small worked examples and one real data set, involving both binary and quantitative response data, to help end-users appreciate the essence of the method. The examples are simple enough to see the behind-the-scenes calculations and the essential role of weighted observations, and they allow nonstatisticians to imagine the calculations involved when the GEE method is applied to more complex multivariate data.
correlation; epidemiologic methods; generalized estimating equation; longitudinal studies; odds ratio; statistics
Abbreviations: Abbreviation: GEE, generalized estimating equations.
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J. H. Godbold RE: "STATISTICAL ANALYSIS OF CORRELATED DATA USING GENERALIZED ESTIMATING EQUATIONS: AN ORIENTATION" Am. J. Epidemiol., August 1, 2003; 158(3): 289 - 289. [Full Text] [PDF]
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G. Zou RE: "STATISTICAL ANALYSIS OF CORRELATED DATA USING GENERALIZED ESTIMATING EQUATIONS: AN ORIENTATION" Am. J. Epidemiol., August 1, 2003; 158(3): 289 - 289. [Full Text] [PDF]
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J. A. Hanley THE FIRST AUTHOR REPLIES Am. J. Epidemiol., August 1, 2003; 158(3): 289 - 290. [Full Text] [PDF]
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