Etzioni R D, Fienberg S E, Gilula Z, Haberman S J
Fred Hutchinson Cancer Center, Seattle.
Stat Methods Med Res. 1994;3(2):179-204. doi: 10.1177/096228029400300205.
In the late 1970s statisticians extended the methods for analysing loglinear and logit models for cross-classified categorical data to incorporate information about the ordinal structure of the categories corresponding to some of the classification variables. In this paper we review one class of such extensions known as association models. We consider association models with and without order restrictions on the parameters and we use these models to answer research questions about several medical examples involving ordered categorical data. We emphasize the interpretation of parameters in the association models and how this relates to the research questions of interest.
20世纪70年代末，统计学家扩展了用于分析交叉分类分类数据的对数线性和对数模型的方法，以纳入与某些分类变量对应的类别的有序结构的信息。在本文中，我们回顾了一类这样的扩展，称为关联模型。我们考虑对参数有和没有顺序限制的关联模型，并使用这些模型来回答关于几个涉及有序分类数据的医学例子的研究问题。我们强调关联模型中参数的解释以及这与感兴趣的研究问题的关系。
