A conservative test for multiple comparison based on highly correlated test statistics

Yoshiyuki Ninomiya, Hironori Fujisawa

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

In genetics, we often encounter a large number of highly correlated test statistics. The most famous conservative bound for multiple comparison is Bonferroni's bound, which is suitable when the test statistics are independent but not when the test statistics are highly correlated. This article proposes a new conservative bound that is easily calculated without multiple integration and is a good approximation when the test statistics are highly correlated. The performance of the proposed method is evaluated by simulation and real data analysis.

Original languageEnglish
Pages (from-to)1135-1142
Number of pages8
JournalBiometrics
Volume63
Issue number4
DOIs
Publication statusPublished - Dec 1 2007

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Multiple Comparisons
Test Statistic
statistics
Statistics
testing
Bonferroni
data analysis
Data analysis
Approximation
Simulation
methodology

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

Cite this

A conservative test for multiple comparison based on highly correlated test statistics. / Ninomiya, Yoshiyuki; Fujisawa, Hironori.

In: Biometrics, Vol. 63, No. 4, 01.12.2007, p. 1135-1142.

Research output: Contribution to journalArticle

Ninomiya, Yoshiyuki ; Fujisawa, Hironori. / A conservative test for multiple comparison based on highly correlated test statistics. In: Biometrics. 2007 ; Vol. 63, No. 4. pp. 1135-1142.
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