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반복이 있는 랜덤화블록 모형에서 정렬방법과 선형위치통계량을 이용한 비모수 검정법

Nonparametric method using aligned method and linear placement statistics in randomized block design with replications

  • 전소영 (가톨릭대학교 의생명.건강과학과) ;
  • 김동재 (가톨릭대학교 의생명.건강과학과)
  • Jeon, Soyoung (Department of Biomedicine.Health Science, The Catholic University of Korea) ;
  • Kim, Dongjae (Department of Biomedicine.Health Science, The Catholic University of Korea)
  • 투고 : 2017.02.08
  • 심사 : 2017.03.20
  • 발행 : 2017.04.30

초록

반복이 있는 랜덤화블록 모형에서의 비모수적 검정 방법에는 Mack과 Skillings (1980)가 제안한 방법이 있다. 이 방법은 각각의 관측값을 사용하는 대신 각 블록에서의 반복된 관측값들의 평균을 사용하여 검정하는 방법이다. 따라서 관측치들의 정보를 손실할 수 있다는 단점이 있다. 본 논문에서는 이러한 단점을 보완하기 위해 정렬방법과 선형 위치통계량을 이용한 비모수 검정법을 제안하였다. 또한 몬테카를로 모의실험(Monte-Carlo Study)을 통하여 기존의 방법과 제안한 방법의 검정력을 비교하였다.

Mack and Skillings (1980) proposed a nonparametric method in a randomized block design with replications. This method employs the mean of observations instead of each observation. However, it has the inherent disadvantage that there may be a loss of information. In this paper, we proposed a nonparametric method that employees an aligned method and linear placement statistics to supplement its weakness. A Monte-Carlo study is performed to compare the power of the proposed method with previous methods.

키워드

참고문헌

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