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Retinopathy of prematurity and beyond: P values don't make risk factors

Olaf Dammann1,2, Kenneth Chui3, Brian K Stansfield4

  • 1Department of Public Health & Community Medicine, Tufts University School of Medicine, Boston, MA, USA. olaf.dammann@tufts.edu.

Pediatric Research
|June 25, 2025
PubMed

Insights

Avoid using P values for determining variable associations. Instead, interpret confidence intervals as compatibility intervals for better decision-making in pediatric clinical epidemiology research.

Area of Science:

  • Epidemiology
  • Biostatistics

Background:

  • P values are frequently misinterpreted in scientific research.
  • Statistical significance is often conflated with practical importance.

Purpose of the Study:

  • To clarify the meaning and appropriate use of P values.
  • To advocate for the use of confidence intervals as compatibility intervals.
  • To improve decision-making in pediatric clinical epidemiology.

Main Methods:

  • Review of statistical interpretation guidelines.
  • Discussion of the limitations of P value thresholds.
  • Explanation of confidence intervals as measures of compatibility.

Main Results:

  • P values do not indicate the probability that a null hypothesis is true.
  • Confidence intervals provide a range of plausible values for an effect size.
  • Compatibility intervals offer a more informative approach than P value dichotomization.

Conclusions:

  • Discourage the use of P values for binary decisions on statistical significance.
  • Promote the interpretation of confidence intervals as compatibility intervals.
  • Enhance the rigor and clarity of statistical reporting in pediatric clinical epidemiology.
Abstract

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