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Goodman-Kruskal Measure of Association for Fuzzy-Categorized Variables
Kybernetika, Tome 47 (2011) no. 1, pp. 110-122 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

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The Goodman-Kruskal measure, which is a well-known measure of dependence for contingency tables, is generalized to the case when the variables of interest are categorized by linguistic terms rather than crisp sets. In addition, to test the hypothesis of independence in such contingency tables, a novel method of decision making is developed based on a concept of fuzzy $p$-value. The applicability of the proposed approach is explained using a numerical example.
The Goodman-Kruskal measure, which is a well-known measure of dependence for contingency tables, is generalized to the case when the variables of interest are categorized by linguistic terms rather than crisp sets. In addition, to test the hypothesis of independence in such contingency tables, a novel method of decision making is developed based on a concept of fuzzy $p$-value. The applicability of the proposed approach is explained using a numerical example.
Classification : 62A10, 93E12
Keywords: fuzzy frequency; fuzzy category; fuzzy Goodman–Kruskal statistic; fuzzy $p$-value; fuzzy significance level; NSD index 
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Taheri, S. M.; Hesamian, G. Goodman-Kruskal Measure of Association for Fuzzy-Categorized Variables. Kybernetika, Tome 47 (2011) no. 1, pp. 110-122. http://geodesic.mathdoc.fr/item/KYB_2011_47_1_a8/

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