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Multiple comparisons: philosophies and illustrations.

D Curran-Everett1

  • 1Departments of Preventive Medicine and Biometrics and of Physiology and Biophysics, School of Medicine, University of Colorado Health Sciences Center, Denver, Colorado 80262, USA. dcurran-@carbon.cudenver.edu

American Journal of Physiology. Regulatory, Integrative and Comparative Physiology
|July 18, 2000
PubMed
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Statistical methods are crucial for scientific discovery. This review highlights the risks of multiple comparisons in research and introduces the false discovery rate procedure as a practical solution.

Area of Science:

  • Physiology
  • Biostatistics
  • Scientific Methodology

Background:

  • Statistical procedures are fundamental to scientific discovery, particularly in testing null hypotheses.
  • Multiple comparisons in research increase the likelihood of erroneous scientific conclusions if not properly managed.
  • Approximately 40% of articles published by the American Physiological Society in 1997 utilized multiple comparison procedures.

Purpose of the Study:

  • To elucidate the statistical challenges inherent in multiple comparisons.
  • To review existing philosophies and methods for addressing multiple comparisons.
  • To introduce and advocate for the false discovery rate procedure as an effective solution.

Main Methods:

  • Literature review of statistical procedures for multiple comparisons.

Related Experiment Videos

  • Analysis of commonly cited methods: Newman-Keuls, Bonferroni, and least significant difference.
  • Demonstration of the False Discovery Rate (FDR) procedure.

    • Main Results:

    • Traditional methods like Newman-Keuls, Bonferroni, and least significant difference have limited practical value for multiple comparisons.
    • The False Discovery Rate (FDR) procedure is presented as a statistically sound and promising approach.
    • FDR offers a superior practical solution for managing multiple comparisons in scientific research.

    Conclusions:

    • Inappropriate handling of multiple comparisons can lead to incorrect scientific conclusions.
    • Established procedures such as Newman-Keuls, Bonferroni, and least significant difference are often inadequate.
    • The False Discovery Rate (FDR) procedure represents a significant advancement and the most practical solution for multiple comparisons across scientific disciplines.