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Moving Beyond Statistical Significance: How to Improve the Reporting and Interpretation of Medical Research

Author

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  • Rovetta, Alessandro

    (International Committee Against the Misuse of Statistical Significance, Bov)

  • Mansournia, Mohammed Ali
  • Msaouel, Pavlos
  • Lin, Winston
  • Stovitz, Steven
  • Vitale, Alessandro
  • Frigo, Anna Chiara
  • Riley, Richard
  • Greenland, Sander

Abstract

Many methodologists have warned against interpreting statistical estimates through dichotomous labels such as “significant” and “non-significant.” Yet, articles in medical journals still rely heavily on P-value thresholds and confidence interval boundaries to guide inference and communication of research findings. Here, Rovetta and colleagues discuss how such a focus on statistical “significance” obscures clinical relevance and uncertainty, whilst distorting evidence appraisals. Rather, they suggest P-values and confidence intervals should be interpreted as continuous measures of compatibility between data and hypotheses, which also reflect choices about how data are collected, modeled, and analyzed.

Suggested Citation

  • Rovetta, Alessandro & Mansournia, Mohammed Ali & Msaouel, Pavlos & Lin, Winston & Stovitz, Steven & Vitale, Alessandro & Frigo, Anna Chiara & Riley, Richard & Greenland, Sander, 2026. "Moving Beyond Statistical Significance: How to Improve the Reporting and Interpretation of Medical Research," MetaArXiv 6xuhr_v1, Center for Open Science.
    • Handle: RePEc:osf:metaar:6xuhr_v1
    DOI: 10.31222/osf.io/6xuhr_v1
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