A Classification Statistic for GEE Categorical Response Models

John M. Williamson, Hung-Mo Lin and Huiman X. Barnhart

Journal of Data Science, v.1, no.2, 149-165.

Abstract

A kappa-like classification statistic is proposed for assessing the fit of GEE regression models with a categorical response. The proposed statistic is a summary measure depicting how well categorical responses are predicted from the fitted GEE model. The statistic takes on a value of 1 if prediction is perfect and a value of 0 if the fitted model fares no better than random chance, i.e., fitting the repeated categorical responses with an intercept-only model. To demonstrate the usefulness of the classification statistic, we present simulation results as well as two examples from biomedical studies.

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