Transcription of Generalized Estimating Equations - SAS
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Generalized Estimating Equations - SAS
Generalized Estimating Equations Introduction The Generalized Estimating Equations (GEEs) methodology, introduced by Liang and Zeger (1986), enables you to analyze correlated data that otherwise could be modeled as a Generalized linear model. GEEs have become an important strategy in the analysis of correlated data. These data sets can arise from longitudinal studies, in which subjects are measured at different points in time, or from clustering, in which measurements are taken on subjects who share a common characteristic, such as belonging to the same litter. SAS/STAT. software provides two procedures that enable you to perform GEE analysis: the GENMOD procedure and the GEE procedure.
CONTRAST, LSMEANS, and ESTIMATE statements alternating logistic regression estimation models for ordinal data The proportional odds model is a popular method of GEE analysis of ordinal data and is based on modeling cumulative logit functions. The GENMOD procedure also models cumulative probits and cumulative complementary log-log functions.
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