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Applications of conditional power function of two-sample permutation test

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dc.contributor.author Samuh, Monjed H.
dc.contributor.author Pesarin, Fortunato
dc.date.accessioned 2019-10-08T11:02:43Z
dc.date.accessioned 2022-05-22T08:52:11Z
dc.date.available 2019-10-08T11:02:43Z
dc.date.available 2022-05-22T08:52:11Z
dc.date.issued 2018-03
dc.identifier.uri http://localhost:8080/xmlui/handle/123456789/8065
dc.description.abstract Permutation or randomization test is a nonparametric test in which the null distribution (distribution under the null hypothesis of no relationship or no effect) of the test statistic is attained by calculating the values of the test statistic overall permutations (or by considering a large number of random permutation) of the observed dataset. The power of permutation test evaluated based on the observed dataset is called conditional power. In this paper, the conditional power of permutation tests is reviewed. The use of the conditional power function for sample size estimation is investigated. Moreover, reproducibility and generalizability probabilities are defined. The use of these probabilities for sample size adjustment is shown. Finally, an illustration example is used. en_US
dc.language.iso en_US en_US
dc.publisher Springer Computational Statistics en_US
dc.subject Generalizability probability, Permutation test, Reproducibility probability, Sample size adjustment, Sample size estimation en_US
dc.title Applications of conditional power function of two-sample permutation test en_US
dc.type Article en_US


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