Local and global cross ratios to model the association between ordinal variables

Abstract

In this paper we present marginal association and regression models as an alternative to classical association models for cross-classified ordinal data. It is shown that the methods easily incorporate various types of association structures, are able to include covariate information and generalize easily to multi-way classifications. The proposed approach is used to analyze data from a multicentre psychiatric study.