Statistical analysis of correlated data using generalized estimating equations: an orientation.
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.
Hanley
James A
JA
Department of Epidemiology and Biostatistics, Faculty of Medicine, McGill University, Montreal, Quebec, Canada. james.hanley@mcgill.ca
Negassa
Abdissa
A
Edwardes
Michael D deB
MD
Forrester
Janet E
JE
D001827:Body Height; D002648:Child; D004812:Epidemiologic Methods; D006801:Humans; D008137:Longitudinal Studies; D015233:Models, Statistical; D012959:Socioeconomic Factors