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Many statisticians have considered various symmetry and asymmetry models to analyze square contingency tables with ordinal categories. We propose a generalized model, which indicates the asymmetric structure for cell probabilities. This model is the closest to the symmetry model in terms of the f-divergence under certain conditions. Then we decompose the symmetry model using the proposed model, and partition the likelihood-ratio chi-square test statistics for the symmetry model. The decomposition is useful to deduce the reason for a poor fit of the symmetry model.
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Fujisawa et al. (2020) studied this question.
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