15.3. Summary of the GEE Methodology
The GEE method is a practical strategy for the analysis of repeated measurements, particularly categorical repeated measurements. It provides a way to handle continuous explanatory variables, a moderate number of explanatory categorical variables, and time-dependent explanatory variables. It handles missing values, that is, the number of measurements in each cluster can vary from 1 to t.
The following are the important properties of the GEE method:
GEEs reduce to GLM estimating equations for ti = 1.
GEEs are the maximum likelihood score equations for multivariate Gaussian data when you specify unstructured correlation.
The regression parameter estimates are consistent as the number of clusters become large, ...
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