The frequent insignificance of a "significant" p-value

J Card Surg. 2021 Nov;36(11):4322-4331. doi: 10.1111/jocs.15960. Epub 2021 Sep 3.

Abstract

Null hypothesis significance testing (NHST) and p-values are widespread in the cardiac surgical literature but are frequently misunderstood and misused. The purpose of the review is to discuss major disadvantages of p-values and suggest alternatives. We describe diagnostic tests, the prosecutor's fallacy in the courtroom, and NHST, which involve inter-related conditional probabilities, to help clarify the meaning of p-values, and discuss the enormous sampling variability, or unreliability, of p-values. Finally, we use a cardiac surgical database and simulations to explore further issues involving p-values. In clinical studies, p-values provide a poor summary of the observed treatment effect, whereas the three-number summary provided by effect estimates and confidence intervals is more informative and minimizes over-interpretation of a "significant" result. p-values are an unreliable measure of the strength of evidence; if used at all they give only, at best, a very rough guide to decision making. Researchers should adopt Open Science practices to improve the trustworthiness of research and, where possible, use estimation (three-number summaries) or other better techniques.

Keywords: Bayes theorem; clinical review; null hypothesis; p values; replication; significance testing.

Publication types

  • Review

MeSH terms

  • Bayes Theorem
  • Humans
  • Probability
  • Research Design*