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A measure of association (correlation) in nominal data (contingency tables), using determinants

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  • Colignatus, Thomas

Abstract

Nominal data currently lack a correlation coefficient, such as has already defined for real data. A measure is possible using the determinant, with the useful interpretation that the determinant gives the ratio between volumes. With M a m × n contingency table and n ≤ m the suggested measure is r = Sqrt[det[A'A]] with A = Normalized[M]. With M an n1 × n2 × ... × nk contingency matrix, we can construct a matrix of pairwise correlations R so that the overall correlation is f[R]. An option is to use f[R] = Sqrt[1 - det[R]]. However, for both nominal and cardinal data the advisable choice for such a function f is to take the maximal multiple correlation within R.

Suggested Citation

  • Colignatus, Thomas, 2007. "A measure of association (correlation) in nominal data (contingency tables), using determinants," MPRA Paper 2662, University Library of Munich, Germany, revised 10 Apr 2007.
  • Handle: RePEc:pra:mprapa:2662
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    Citations

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    Cited by:

    1. Colignatus, Thomas, 2017. "Comparing votes and seats with a diagonal (dis-) proportionality measure, using the slope-diagonal deviation (SDD) with cosine, sine and sign," MPRA Paper 80965, University Library of Munich, Germany, revised 24 Aug 2017.
    2. Colignatus, Thomas, 2007. "The 2 x 2 x 2 case in causality, of an effect, a cause and a confounder. A cross-over’s guide to the 2 x 2 x 2 contingency table," MPRA Paper 3351, University Library of Munich, Germany, revised 14 May 2007.
    3. Colignatus, Thomas, 2017. "Comparing votes and seats with a diagonal (dis-) proportionality measure, using the slope-diagonal deviation (SDD) with cosine, sine and sign," MPRA Paper 80833, University Library of Munich, Germany, revised 17 Aug 2017.
    4. Colignatus, Thomas, 2018. "An overview of the elementary statistics of correlation, R-squared, cosine, sine, and regression through the origin, with application to votes and seats for Parliament," MPRA Paper 84722, University Library of Munich, Germany, revised 20 Feb 2018.

    More about this item

    Keywords

    association; correlation; contingency table; volume ratio; determinant; nonparametric methods; nominal data; nominal scale; categorical data; Fisher’s exact test; odds ratio; tetrachoric correlation coefficient; phi; Cramer’s V; Pearson; contingency coefficient; uncertainty coefficient; Theil’s U; eta; meta-analysis; Simpson’s paradox; causality; statistical independence;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General

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