ANALYSIS OF LONGITUDINAL ORDERED POLYTOMOUS DATA USING GENERALIZED ESTIMATING EQUATIONS

Abstract

A model for the analysis of repeated ordered polytomous data using the generalized estimating equations(GEE)method is presented. Our model is a direct extension of McCullagh's model(1980)for longitudinal data. For independence estimating equations, this model is equivalent to the models proposed by Miller et al.(1993)and Lipsitz et al.(1994). When one extends this model to allow for correlated observation, our model is not equivalent to theirs. Furthermore, our model can estimate the correlations using a simpler working covariance matrix in the second set of estimating equations than that of Miller et al., and it allows for the use of the AR(1)correlation structure, which is not possible using either of the others. Two examples of the analyses of longitudinal ordered polytomous data are given, one for judgmental ordinal data and the other for grouped continuous ordinal data. Among several working correlation models, a relatively simple working correlation structure suffices for each data set.