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Shannon entropy type measure of departure from uniform association in cross-classifications having ordered categories

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  • Tomizawa, Sadao

Abstract

A measure is proposed to represent the degree of departure from uniform association in cross-classifications having ordered categories. The measure is expressed by using the Shannon entropy or the Kullback-Leibler information, based on the local odds ratios. It would be useful when one wants to use a single summary measure to measure distance of the local odds ratios from uniformity.

Suggested Citation

  • Tomizawa, Sadao, 1991. "Shannon entropy type measure of departure from uniform association in cross-classifications having ordered categories," Statistics & Probability Letters, Elsevier, vol. 11(6), pages 547-550, June.
    • Handle: RePEc:eee:stapro:v:11:y:1991:i:6:p:547-550
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    Cited by:

    1. Conde, J. & Salicrú, M., 1998. "Uniform association in contingency tables associated to Csiszar divergence," Statistics & Probability Letters, Elsevier, vol. 37(2), pages 149-154, February.
    2. Alba-Fernández, V. & Jiménez-Gamero, M.D., 2011. "Estimating Rao’s statistic distribution for testing uniform association in cross-classifications," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(10), pages 1978-1990.

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