A guide for authors and readers of the American Society for Nutrition Journals on the proper use of P values and strategies that promote transparency and improve research reproducibility

Am J Clin Nutr. 2021 Oct 4;114(4):1280-1285. doi: 10.1093/ajcn/nqab223.

Abstract

Two questions regarding the scientific literature have become grist for public discussion: 1) what place should P values have in reporting the results of studies? 2) How should the perceived difficulty in replicating the results reported in published studies be addressed? We consider these questions to be 2 sides of the same coin; failing to address them can lead to an incomplete or incorrect message being sent to the reader. If P values (which are derived from the estimate of the effect size and a measure of the precision of the estimate of the effect) are used improperly, for example reporting only significant findings, or reporting P values without account for multiple comparisons, or failing to indicate the number of tests performed, the scientific record can be biased. Moreover, if there is a lack of transparency in the conduct of a study and reporting of study results, it will not be possible to repeat a study in a manner that allows inferences from the original study to be reproduced or to design and conduct a different experiment whose aim is to confirm the original study's findings. The goal of this article is to discuss how P values can be used in a manner that is consistent with the scientific method, and to increase transparency and reproducibility in the conduct and analysis of nutrition research.

Keywords: P value; reliability; reproducibility; strategies; transparency.

Publication types

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

MeSH terms

  • Disclosure*
  • Editorial Policies
  • Humans
  • Nutritional Sciences*
  • Periodicals as Topic*
  • Publishing / standards*
  • Reproducibility of Results*
  • Research Design* / statistics & numerical data
  • United States