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.

Autor: 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, Duggan, Christopher P, Tobias, Deirdre K
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Zdroj: American Journal of Clinical Nutrition; Oct2021, Vol. 114 Issue 4, p1280-1285, 6p, 1 Chart, 2 Graphs
Abstrakt: 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. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index