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On reporting and interpreting statistical significance and p values in medical research
  1. Herman Aguinis1,
  2. Matt Vassar2,
  3. Cole Wayant2
  1. 1Management, The George Washington University, Washington, District of Columbia, USA
  2. 2Psychiatry and Behavioral Sciences, Oklahoma State University Center for Health Sciences, Tulsa, Oklahoma, USA
  1. Correspondence to Cole Wayant, Oklahoma State University Center for Health Sciences, Tulsa, OK 74107, USA; cole.wayant{at}

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Recent proposals to change the p value threshold from 0.05 to 0.005 or to retire statistical significance altogether have garnered much criticism and debate.1 2 As of the writing of our manuscript, the proposal to eliminate statistical significance testing, backed by over 800 signatories, achieved record-breaking status on Altmetrics, with an attention score exceeding 13 000 derived from 19 000 Twitter comments and 35 news stories. We appreciate the renewed enthusiasm for tackling important issues related to the analysis, reporting and interpretation of scientific research results. Our perspective, however, focuses on the current use and reporting of statistical significance and where we should go from here.

  1. We begin by saying that p values themselves are not flawed. Rather, the use, misuse or abuse of p values in ways antithetical to rigorous scientific pursuits is the flaw. If p values are a hammer, scientists are the hammer wielders. One would not discard the hammer if the wielder, when using the hammer, repeatedly missed the nail. Similarly, one would not discard the hammer if the wielder used the hammer in a way not suited to the hammer’s purpose, such as in an attempt to drive a screw. Rather, one would expect that the fault lies with the hammer-wielder and recommend ways to refine the hammer’s use. Thus, a focus on …

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