Analyzing an ordinal pharmaceutical data set with a categorical covariate using monotone-scores models

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Abstract
Chuang and Agresti (1986) propose a monotone-scores model to analyze an ordinal pain data set from a pharmaceutical study where 4 analgesics were compared for their pain-relieving capabilities. In this paper, we generalize the model of Chuang and Agresti to incorporate an additional pre-test categorical variable. This generalization allows an ordering of the drugs conditional on a subject's pre-test categorical presentation. It also allows the identification of subjects who can most benefit from different drugs under comparison. These extensions are applied to part of a CNS study where an active drug was compared to a placebo and a pre-medication response to a placebo was available.