What is the chance that this study is clinically significant? A proposal for Q values

Eff Clin Pract. Sep-Oct 1999;2(5):234-9.

Abstract

Context: Clinicians who use the medical literature to guide their practice need to make judgments about the clinical significance of medical interventions.

General question: How likely is an intervention to be clinically worthwhile?

Specific research challenge: Given the results of a study, determining the probability that the true effect of an intervention is at least as great as some minimum worthwhile effect.

Current approach: P values are widely used to convey the probability of observed effects arising by chance if there truly is no effect. By convention, P values less than 0.05 are interpreted as being "statistically significant."

Potential difficulties: Statistical significance is often confused with clinical significance.

Alternate approach: A different probability could be reported, a probability I call a Q value. A Q value is the probability that the true effect of an intervention is at least as great as some minimum worthwhile effect. Q values are calculated in a manner analogous to that used for P values, except that the null hypothesis becomes a minimum worthwhile effect instead of no effect. Q values encourage researchers and clinicians to be explicit about what they think a worthwhile effect is and could help shift the focus of study interpretation away from arbitrary statistical conventions.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Clinical Trials as Topic
  • Confidence Intervals
  • Evidence-Based Medicine*
  • Models, Statistical*
  • Practice Patterns, Physicians'
  • Treatment Outcome
  • United States