Comparative Analysis for Multiple Testing Procedures with Binary Data

• 발행기관: 한국자료분석학회
• 저자명: 곽민정(Minjung Kwak) 이학배(Hakbae Lee) 윤민(Min Yoon)
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.17 No.1, 1~8쪽, 전체 8쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2015.02.28

영문 초록

Multiplicity problems frequently arise in data analysis. We review the multiple testing procedures with binary data. Especially with binary data, discreteness and ignorance of correlation structures in adjustment of multiplicity result in the loss of power. We review single step tests and stepwise tests as multiple testing procedures. We discuss single step tests such as Bonferroni and Sidak procedures and more powerful stepwise closed testing procedures such as the Holm and Hochberg procedures. We also, provide an overview of the methods of resampling-based multiplicity adjustment introduced by Westfall, Young (1993) and discuss the subset pivotality condition in discrete distribution. Multiple testing procedures are compared through simulation study and familywise error rates of these methods are presented. The familywise error rates of all multiple testing procedures do not exceed the nominal level. Among multiple testing procedures, the resampling-based methods are less conservative than single step tests and stepwise tests.

목차

1. Introduction

2. Multiple Testing Procedures

3. Resampling-Based Testing Procedures

4. Simulation Study

5. Conclusion

References

키워드

Multiplicity Familywise error rate Multiple testing procedure Resampling- based multiple test