Literature DB >> 34258613

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.

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


  9 in total

1.  More powerful procedures for multiple significance testing.

Authors:  Y Hochberg; Y Benjamini
Journal:  Stat Med       Date:  1990-07       Impact factor: 2.373

2.  Comparing individual means in the analysis of variance.

Authors:  J W TUKEY
Journal:  Biometrics       Date:  1949-06       Impact factor: 2.571

3.  New Guidelines for Statistical Reporting in the Journal.

Authors:  David Harrington; Ralph B D'Agostino; Constantine Gatsonis; Joseph W Hogan; David J Hunter; Sharon-Lise T Normand; Jeffrey M Drazen; Mary Beth Hamel
Journal:  N Engl J Med       Date:  2019-07-18       Impact factor: 91.245

Review 4.  Best practices in nutrition science to earn and keep the public's trust.

Authors:  Cutberto Garza; Patrick J Stover; Sarah D Ohlhorst; Martha S Field; Robert Steinbrook; Sylvia Rowe; Catherine Woteki; Eric Campbell
Journal:  Am J Clin Nutr       Date:  2019-01-01       Impact factor: 7.045

Review 5.  The Challenge of Reproducibility and Accuracy in Nutrition Research: Resources and Pitfalls.

Authors:  Barbara C Sorkin; Adam J Kuszak; John S Williamson; D Craig Hopp; Joseph M Betz
Journal:  Adv Nutr       Date:  2016-03-15       Impact factor: 8.701

6.  Scientific rigor and credibility in the nutrition research landscape.

Authors:  Cynthia M Kroeger; Cutberto Garza; Christopher J Lynch; Esther Myers; Sylvia Rowe; Barbara O Schneeman; Arya M Sharma; David B Allison
Journal:  Am J Clin Nutr       Date:  2018-03-01       Impact factor: 7.045

7.  Interaction between genes and macronutrient intake on the risk of developing type 2 diabetes: systematic review and findings from European Prospective Investigation into Cancer (EPIC)-InterAct.

Authors:  Sherly X Li; Fumiaki Imamura; Zheng Ye; Matthias B Schulze; Jusheng Zheng; Eva Ardanaz; Larraitz Arriola; Heiner Boeing; Courtney Dow; Guy Fagherazzi; Paul W Franks; Antonio Agudo; Sara Grioni; Rudolf Kaaks; Verena A Katzke; Timothy J Key; Kay Tee Khaw; Francesca R Mancini; Carmen Navarro; Peter M Nilsson; N Charlotte Onland-Moret; Kim Overvad; Domenico Palli; Salvatore Panico; J Ramón Quirós; Olov Rolandsson; Carlotta Sacerdote; María-José Sánchez; Nadia Slimani; Ivonne Sluijs; Annemieke Mw Spijkerman; Anne Tjonneland; Rosario Tumino; Stephen J Sharp; Elio Riboli; Claudia Langenberg; Robert A Scott; Nita G Forouhi; Nicholas J Wareham
Journal:  Am J Clin Nutr       Date:  2017-06-07       Impact factor: 7.045

8.  Standardization of laboratory practices and reporting of biomarker data in clinical nutrition research.

Authors:  Karen M O'Callaghan; Daniel E Roth
Journal:  Am J Clin Nutr       Date:  2020-05-20       Impact factor: 7.045

9.  Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations.

Authors:  Sander Greenland; Stephen J Senn; Kenneth J Rothman; John B Carlin; Charles Poole; Steven N Goodman; Douglas G Altman
Journal:  Eur J Epidemiol       Date:  2016-05-21       Impact factor: 8.082

  9 in total
  3 in total

1.  Reply to Verhoef et al.

Authors:  John D Sorkin; Mark Manary; Paul A M Smeets; Amanda J MacFarlane; Arne Astrup; Ronald L Prigeon; Beth B Hogans; Jack Odle; Teresa A Davis; Katherine L Tucker; Christopher P Duggan; Deirdre K Tobias
Journal:  Am J Clin Nutr       Date:  2022-02-09       Impact factor: 7.045

2.  ASN guidelines on P values.

Authors:  Hans Verhoef; Edith Feskens; Pieter van 't Veer; Andrew M Prentice
Journal:  Am J Clin Nutr       Date:  2022-02-09       Impact factor: 7.045

3.  Heterogeneity in Meat Food Groups Can Meaningfully Alter Population-Level Intake Estimates of Red Meat and Poultry.

Authors:  Lauren E O'Connor; Kirsten A Herrick; Ruth Parsons; Jill Reedy
Journal:  Front Nutr       Date:  2021-12-15
  3 in total

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