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Statistically Proper Multiple Range Tests for a Within Subject Factor in a Repeated Measures Design
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  • Statistically Proper Multiple Range Tests for a Within Subject Factor in a Repeated Measures Design
  • Statistically Proper Multiple Range Tests for a Within Subject Factor in a Repeated Measures Design
저자명
Park. Cheol-Yong,Park. Sang-Bum
간행물명
한국데이터정보과학회지
권/호정보
2007년|18권 2호|pp.525-534 (10 pages)
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한국데이터정보과학회
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정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

It is a common practice in many research areas that multiple range tests for a between subject factor such as Tukey are applied to a within subject factor in a repeated measures design. Tukey procedure, however, sometimes detects no pairs with different means even when the hypothesis of all equal level means is rejected. This study attempts to provide a rationale for the proposition that Tukey is inappropriate post hoc procedure for a within subject factor in which the observations are correlated. We introduce two multiple range tests, Bonferroni and Scheffe, for a within subject factor and show that Bonferroni is more appropriate than Scheffe for pairwise multiple comparisons. Subsequent simulation study indicates that Tukey has significantly less power than Bonferroni in detecting actual difference between means of some pairs when the observations of a within subject factor are highly correlated.