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All-pairs multiple comparisons based on the Cucconi test

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  • Hidetoshi Murakami

    (Tokyo University of Science)

Abstract

One-way design nonparametric multiple comparison problems are among the most important topics in nonparametric statistics. Various nonparametric tests have been proposed and considered for a multiple comparison problems by many authors over the years. The analysis of one-way design multiple comparisons are important in biometry. Nonparametric all-pairs multiple comparisons based on pairwise rankings are considered in the one-way layout. The pairwise ranking test based on the Cucconi test for the one-way layout multiple comparison of the location-scale problem is proposed. Simulations are used to investigate the power of the proposed test for jointly location and scale alternatives with various population distributions for small sample sizes. The suggested method is illustrated by the analysis of real data.

Suggested Citation

  • Hidetoshi Murakami, 2016. "All-pairs multiple comparisons based on the Cucconi test," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 100(3), pages 355-368, July.
    • Handle: RePEc:spr:alstar:v:100:y:2016:i:3:d:10.1007_s10182-016-0268-x
    DOI: 10.1007/s10182-016-0268-x
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    References listed on IDEAS

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    1. Marco Marozzi, 2014. "The multisample Cucconi test," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 209-227, June.
    2. Shan, Guogen & Ma, Changxing & Hutson, Alan D. & Wilding, Gregory E., 2013. "Some tests for detecting trends based on the modified Baumgartner–Weiß–Schindler statistics," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 246-261.
    3. Murakami, Hidetoshi, 2007. "Lepage type statistic based on the modified Baumgartner statistic," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 5061-5067, June.
    Full references (including those not matched with items on IDEAS)

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