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다변량 분산분석에서 개선된 비모수적 붓스트랩 방법Modified Nonparametric Bootstrap Method in MANOVA

Other Titles
Modified Nonparametric Bootstrap Method in MANOVA
Authors
유기상진서훈
Issue Date
2017
Publisher
대한설비관리학회
Keywords
MANOVA; Nonparametric Method; Bootstrap Method
Citation
대한설비관리학회지, v.22, no.4, pp.87 - 93
Indexed
KCI
Journal Title
대한설비관리학회지
Volume
22
Number
4
Start Page
87
End Page
93
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/85317
ISSN
1598-2475
Abstract
In general, MANOVA that verifies the relationship between two or more continuous dependent variables and categorical independent variables is possible when the assumption of multivariate normality, equal variances, and sphericity assumption. However, most of the actual data that can be obtained, especially a small number of sample data are difficult to meet the above assumptions. Therefore, since the results of the analysis by the parametric method are difficult to be relied upon, mainly the bootstrap method has been studied as a nonparametric approach. Konietschke et al.[3] presented a parametric and nonparametric bootstrap method that can be used in small sample sizes that do not satisfy the assumptions of multivariate normality and equal variances. However, due to the resampling method which ignores treatment groups, there is a problem that the bootstrap distribution of test statistic under the null hypothesis is different from the theoretically approximated distribution when null hypotheses is untrue. In order to solve these problems, we propose a nonparametric bootstrap method that resamples residuals from each treatment group. The proposed method shows that even if the null hypothesis is not satisfied, theoretically approximated distribution and bootstrap distribution are similar. We also confirmed that the results of the proposed method are improved over the existing methods through the example data.
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