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Cumulative correspondence analysis using orthogonal polynomials

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  • Antonello D'Ambra

Abstract

Taguchi'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.

Suggested Citation

  • Antonello D'Ambra, 2017. "Cumulative correspondence analysis using orthogonal polynomials," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(6), pages 2942-2954, March.
    • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:6:p:2942-2954
    DOI: 10.1080/03610926.2015.1053938
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