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Related Experiment Videos

A proposal for interpreting and reporting negative studies.

W W Hauck, S Anderson

    Statistics in Medicine
    |May 1, 1986
    PubMed
    Summary
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    This study introduces equivalence testing as a superior method for interpreting negative studies. It quantifies actual study findings, unlike traditional design-power methods.

    Area of Science:

    • Biostatistics
    • Clinical Trials
    • Epidemiology

    Background:

    • Interpreting 'negative' studies (those without statistically significant differences) remains a challenge.
    • The conventional design-power method assesses a study's potential to detect differences, not its actual findings.
    • This can lead to ambiguity in reporting study outcomes.

    Purpose of the Study:

    • To propose and illustrate equivalence testing as an alternative to the design-power method for analyzing negative studies.
    • To provide a quantitative approach for interpreting study results by defining equivalence within specified limits.
    • To offer methods for summarizing results when a priori limits cannot be set.

    Main Methods:

    • Equivalence testing is applied, defining equivalence as the actual difference falling within predefined limits.

    Related Experiment Videos

  • This approach quantifies study outcomes using p-values, focusing on what was determined.
  • Illustrative examples are provided using a cancer clinical trial and an epidemiologic case-control study.

    • Main Results:

    • Equivalence testing offers a direct measure of the observed difference, unlike the indirect assessment of power.
    • A potential outcome is concluding that means or proportions do not differ by more than a specified amount at a given significance level (e.g., 5%).
    • Equivalence curves are proposed for studies lacking a priori equivalence limits.

    Conclusions:

    • Equivalence testing provides a more informative interpretation of negative studies by quantifying actual findings.
    • This method is applicable across various study designs, enhancing the reporting of research outcomes.
    • The use of equivalence testing and curves improves the clarity and precision of scientific communication.