title: What is the value of a p value?
abstract: Successful publication of a research study usually requires a small p value, typically p < 0.05. Many clinicians believe that a p value represents the probability that the null hypothesis is true, so that a small p value means the null hypothesis must be false. In fact, the p value provides very weak evidence against the null hypothesis, and the probability that the null hypothesis is true is usually much greater than the p value would suggest. Moreover, even considering "the probability that the null hypothesis is true" is not possible with the usual statistical setup and requires a different (Bayesian) statistical approach. We describe the Bayesian approach using a well-established diagnostic testing analogy. Then, as a practical example, we compare the p-value result of a study of aprotinin-associated operative mortality with the more illuminative interpretation of the same study data using a Bayesian approach.
authors.affiliation: Medical Data Research Center, Providence Health & Services, Portland, Oregon, USA.
authors.forename: Gary L
authors.initials: GL
authors.lastname: Grunkemeier
authors.forename: YingXing
authors.initials: Y
authors.lastname: Wu
authors.forename: Anthony P
authors.initials: AP
authors.lastname: Furnary
mesh_terms: D001699:Biometry; D003327:Coronary Disease / Q000175:diagnosis; D005716:Game Theory; D006801:Humans; D011336:Probability; D015203:Reproducibility of Results; D012106:Research / Q000592:standards*; D012307:Risk Factors; D012680:Sensitivity and Specificity