• 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

      Sorkin, John D; Manary, Mark; Smeets, Paul A M; MacFarlane, Amanda J; Astrup, Arne; Prigeon, Ronald L; Hogans, Beth B; Odle, Jack; Davis, Teresa A; Tucker, Katherine L; et al. (Oxford University Press, 2021-07-13)
      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.