Abstract
An extension of a bivariate probit model is presented for bivariate polychotomous ordered categorical responses. A linear model is considered on the assumption that the observed categorical variables are manifestations of the latent continuous variables having bivariate normal distributions. Method of inference and analytical procedures are given on the basis of the maximum likelihood procedure. Various applications are discussed and illustrated with examples. The model can be applied to analysis of association, paired comparison, matched pair experiments, testing homogeneity of marginal distributions and symmetry of a square table, factorial analysis with bivariate ordered categorical responses, and so on.
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