Association Models and the Bivariate Normal for Contingency Tables with Ordered Categories
本文以不同形式呈现Goodman(1979)的有序分类列联表关联模型，便于与二元正态分布比较，为四格相关和多格相关提供替代方法，并展示其一般用途。
Association models considered by Goodman (1979) for contingency tables with ordered categories are presented here in a somewhat different form to facilitate comparison with the bivariate normal. Association models can be applied when an underlying bivariate normal is assumed and also under more general conditions, and they provide alternatives to tetrachoric and polychoric correlation. These models agree more closely with the bivariate normal than does Plackett's model (1965), when the row and column classifications arise from underlying univariate normal distributions. The general utility of the association models is illustrated here.