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Generalized Estimation Equations (GEE) are a well-known method for theanalysis of categorical longitudinal responses. GEE method has computationalsimplicity and population parameter interpretation. In the presence of missingdata it is only valid under the strong assumption of missing completely atrandom. A doubly robust estimator (DRGEE) for correlated ordinal longitudinaldata is a nice approach for handling intermittently missing response andcovariate under the MAR mechanism. Independent working correlation is thestandard way in DRGEE. However, when covariate is not time stationary,efficiency can be gained using a structured association. The goal of this paperis to extend the DRGEE estimator to allow modeling the association structure bymeans of either the correlation coefficient or local odds ratio. Simulationresults revealed better performance of the local odds ratio parametrization,specially for small samples. The method is applied to a data set related toRheumatic Mitral Stenosis.

Modeling the Association Structure in Doubly Robust GEE for Longitudinal Ordinal Missing Data