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Five Nonobvious Changes in Editorial Practice for Editors and Reviewers to Consider When Evaluating Submissions in a Post p

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  • David Trafimow

Abstract

The American Statistical Association’s Symposium on Statistical Inference (SSI) included a session on how editorial practices should change in a universe no longer dominated by null hypothesis significance testing (NHST). The underlying assumptions were first, that NHST is problematic; and second, that editorial practices really should change. The present article is based on my talk in this session, and on these assumptions. Consistent with the spirit of the SSI, my focus is not on what reviewers and editors should not do (e.g., NHST) but rather on what they should do, with an emphasis on changes that are not obvious. The recommended changes include a wider consideration of the nature of the contribution than submitted manuscripts usually receive; a greater tolerance of ambiguity; more of an emphasis on the thinking and execution of the study, with a decreased emphasis on the findings; replacing NHST with the a priori procedure; and a call for reviewers and editors to recognize that there are many cases where the basic assumptions of inferential statistical procedures simply are not met, and that inferential statistics (even the a priori procedure) may consequently be inappropriate.

Suggested Citation

  • David Trafimow, 2019. "Five Nonobvious Changes in Editorial Practice for Editors and Reviewers to Consider When Evaluating Submissions in a Post p," The American Statistician, Taylor & Francis Journals, vol. 73(S1), pages 340-345, March.
  • Handle: RePEc:taf:amstat:v:73:y:2019:i:s1:p:340-345
    DOI: 10.1080/00031305.2018.1537888
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    Cited by:

    1. Stef, Nicolae & Zenou, Emmanuel, 2021. "Management-to-staff ratio and a firm's exit," Journal of Business Research, Elsevier, vol. 125(C), pages 252-260.
    2. Hirschauer, Norbert & Grüner, Sven & Mußhoff, Oliver & Becker, Claudia & Jantsch, Antje, 2020. "Can p-values be meaningfully interpreted without random sampling?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 14, pages 71-91.
    3. David J. Hand, 2022. "Trustworthiness of statistical inference," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(1), pages 329-347, January.
    4. Trafimow, David & Hyman, Michael R. & Kostyk, Alena, 2020. "The (im)precision of scholarly consumer behavior research," Journal of Business Research, Elsevier, vol. 114(C), pages 93-101.

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