Abstract

First, basic statistics for treating the association in two-way contingency tables are discussed through information theory. Logarithms of odds, odds ratios, and relative risks in the contingency tables are interpreted as changes of information in the categorical variables concerned. Second, the entropy correlation coefficient (ECC) is introduced for binary variables and the relation between the ECC and the Pearson chi-square statistic for testing the independence between the binary variables is explained. Third, for analyzing the association in general two-way contingency tables, the RC (M) association model is considered. Properties of the model are discussed from a viewpoint of entropy, and ECC is extended for analyzing the association in the RC (M) association model.

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