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Title: Asymmetric dependence modeling for contingency table with an ordinal dependent variable Authors:  Zheng Wei - University of Maine (United States) [presenting]
Daeyoung Kim - University of Massachusetts Amherst (United States)
Li Wang - University of Massachusetts Amherst (United States)
Abstract: For the analysis of a contingency table with an ordinal dependent variable, a subcopula based asymmetric association measure is developed. The subcopula regression-based association measure exploits the subcopula regression to quantify the strength of the association structure in a model-free manner. Unlike the existing measures of asymmetric association, the subcopula-based measure is insensitive to the number of categories in a variable, and thus, the magnitude of the proposed measure can be interpreted as the degree of asymmetric association in the contingency table. The methodology consists of subcopula score, subcopula regression, subcopula regression-based association measure and its decompositions. The sequential decompositions of the proposed association measure evaluate the contribution of the subsets of independent variables to the overall association in various forms.