Ordinal Association in Contingency Tables: Some Interpretive Aspects
研究了Goodman关联模型和典型相关模型这两类用于有序列联表的模型，发现它们分别对应不同类型的序数关联：随机顺序极端性和随机顺序熵，这种差异在强关联下影响显著。
Abstract Two families of models for ordered contingency tables—Goodman's association models and canonical correlation models—are investigated and compared with respect to the interpretation of their parameters. We show that the two families of models actually refer to different kinds of ordinal association: stochastic order extremity for correlation models and stochastic order entropy for association models. This difference is related to the way the two models scale interaction. The scale difference is proven to be of substantial consequence, especially under strong association.