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An algorithm for construction of multiple hypothesis testing

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  • Koon-Shing Kwong

    (National University of Singapore)

Abstract

Summary Recently, the Simes method for constructing multiple hypothesis tests involving multivariate distributions of the test statistics with a particular form of positive dependence has been proved to strongly control the Type I familywise error rate. In this paper, an algorithm is provided so that distributions of ordered test statistics with certain correlation structures can be exactly and efficiently evaluated. Therefore, in some multiple hypothesis testing we can apply the algorithm to obtain tests which are more powerful than the conservative tests based on the Simes method. An example of how to apply the algorithm to the step-up multiple test procedure with a control treatment is presented.

Suggested Citation

  • Koon-Shing Kwong, 2001. "An algorithm for construction of multiple hypothesis testing," Computational Statistics, Springer, vol. 16(1), pages 165-171, March.
    • Handle: RePEc:spr:compst:v:16:y:2001:i:1:d:10.1007_s001800100057
    DOI: 10.1007/s001800100057
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    References listed on IDEAS

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    1. Dunnett, Charles W. & Tamhane, Ajit C., 1993. "Power comparisons of some step-up multiple test procedures," Statistics & Probability Letters, Elsevier, vol. 16(1), pages 55-58, January.
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    Cited by:

    1. Kwong, Koon-Shing & Chan, Yiu-Man, 2008. "On the evaluation of the joint distribution of order statistics," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5091-5099, August.
    2. Kwong, Koon-Shing & Wong, Ee-Hwee, 2002. "A more powerful step-up procedure for controlling the false discovery rate under independence," Statistics & Probability Letters, Elsevier, vol. 56(2), pages 217-225, January.

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