How to understand and teach P values: a diagnostic test framework. Review uri icon

Overview

abstract

  • OBJECTIVES: The aim of the tutorial is to help educators address misconceptions about P values and provide a tool that can be used to teach a more contemporary interpretation. STUDY DESIGN AND SETTING: A scripted tutorial using problem-based learning and a diagnostic test analogy to deconstruct the misunderstandings about P values and develop a more Bayesian approach to study interpretation. RESULTS: A diagnostic test analogy is an effective teaching tool. Learners' understanding of Bayes' theorem in diagnostic testing can be used as a bridge to the realization that the prestudy probability of a true difference is crucial for study interpretation. The analogy has several caveats and shortcomings. The limitations of this analogy and the conceptual difficulties with the Bayesian study analyses are addressed. CONCLUSION: P values do not provide the information many assume they do-they are not equivalent to a probability of a chance finding. This tutorial helps move learners from these incorrect notions to new insights.

publication date

  • March 10, 2020

Research

keywords

  • Biomedical Research
  • Clinical Decision-Making
  • Data Interpretation, Statistical
  • Diagnostic Tests, Routine
  • Guidelines as Topic
  • Probability
  • Research Personnel

Identity

Scopus Document Identifier

  • 85082846024

Digital Object Identifier (DOI)

  • 10.1016/j.jclinepi.2020.03.003

PubMed ID

  • 32169596

Additional Document Info

volume

  • 122