• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.175-182
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• 2020

Fisher's classical method for combining independent p-values from continuous distributions is widely used but it is known to be inadequate for combining p-values from discrete probability distributions. Instead, the discrete analog of Fisher's classical method is used as an alternative for combining p-values from discrete distributions. In this paper, firstly we obtain p-values from discrete probability distributions associated with multi-sample location test data (Fisher-Pitman test and Kruskall-Wallis test data) by permutation method, and secondly combine the permutaion p-values by the discrete analog of Fisher's classical method. And we finally compare the combined p-values from both the discrete analog of Fisher's classical method and Fisher's classical method.

• Communications for Statistical Applications and Methods
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• v.4 no.1
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• pp.41-47
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• 1997

본 연구의 목적은 p변량 관측지가 등상관구조를 갖는 경우 주변분산들의 균일성을 검정하는 통계적 절차를 개발하는 것이다. 이를 위하여 2변량의 경우에 적용되는 피트만(Pitman)의 방법을 3변량 이상의 경우로 확장하고 피셔(Fisher)의 임의화 검정을 적용하여 정규분포의 틀에 의존하지 않는 p 값을 산출한다.