| Literature DB >> 34258613 |
John D Sorkin1,2, Mark Manary3, Paul A M Smeets4, Amanda J MacFarlane5,6, Arne Astrup7, Ronald L Prigeon8, Beth B Hogans1,9, Jack Odle10, Teresa A Davis11, Katherine L Tucker12, Christopher P Duggan13,14, Deirdre K Tobias15,16.
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. Published by Oxford University Press on behalf of the American Society for Nutrition 2021.Entities:
Keywords: zzm321990 P value; reliability; reproducibility; strategies; transparency
Mesh:
Year: 2021 PMID: 34258613 PMCID: PMC8488872 DOI: 10.1093/ajcn/nqab223
Source DB: PubMed Journal: Am J Clin Nutr ISSN: 0002-9165 Impact factor: 8.472