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• W2325331388 abstract "ABSTRACTTaguchi's statistic has long been known to be a more appropriate measure of association of the dependence for ordinal variables compared to the Pearson chi-squared statistic. Therefore, there is some advantage in using Taguchi's statistic in the correspondence analysis context when a two-way contingency table consists at least of an ordinal categorical variable. The aim of this paper, considering the contingency table with two ordinal categorical variables, is to show a decomposition of Taguchi's index into linear, quadratic and higher-order components. This decomposition has been developed using Emerson's orthogonal polynomials. Moreover, two case studies to explain the methodology have been analyzed." @default.
• W2325331388 created "2016-06-24" @default.
• W2325331388 creator A5032598364 @default.
• W2325331388 date "2016-04-11" @default.
• W2325331388 modified "2023-09-25" @default.
• W2325331388 title "Cumulative correspondence analysis using orthogonal polynomials" @default.
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• W2325331388 doi "https://doi.org/10.1080/03610926.2015.1053938" @default.
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