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New-day statistical thinking: A bold proposal for a radical change in practices

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  • Arjen Witteloostuijn

    (Vrije Universiteit Amsterdam)

Abstract

In this commentary, I argue why we should stop engaging in null hypothesis statistical significance testing altogether. Artificial and misleading it may be, but we know how to play the p value threshold and null hypothesis-testing game. We feel secure; we love the certainty. The fly in the ointment is that the conventions have led to questionable research practices. Wasserstein, Schirm, & Lazar (Am Stat 73(sup1):1–19, 2019. https://doi.org/10.1080/00031305.2019.1583913) explain why, in their thought-provoking editorial introducing a special issue of The American Statistician: “As ‘statistical significance’ is used less, statistical thinking will be used more.” Perhaps we empirical researchers can together find a way to work ourselves out of the straitjacket that binds us.

Suggested Citation

  • Arjen Witteloostuijn, 2020. "New-day statistical thinking: A bold proposal for a radical change in practices," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 51(2), pages 274-278, March.
    • Handle: RePEc:pal:jintbs:v:51:y:2020:i:2:d:10.1057_s41267-019-00288-8
    DOI: 10.1057/s41267-019-00288-8
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    References listed on IDEAS

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    1. Andreas Schwab & Eric Abrahamson & William H. Starbuck & Fiona Fidler, 2011. "PERSPECTIVE---Researchers Should Make Thoughtful Assessments Instead of Null-Hypothesis Significance Tests," Organization Science, INFORMS, vol. 22(4), pages 1105-1120, August.
    2. Sander Greenland, 2019. "Valid P-Values Behave Exactly as They Should: Some Misleading Criticisms of P-Values and Their Resolution With S-Values," The American Statistician, Taylor & Francis Journals, vol. 73(S1), pages 106-114, March.
    3. Steven N. Goodman, 2019. "Why is Getting Rid of P-Values So Hard? Musings on Science and Statistics," The American Statistician, Taylor & Francis Journals, vol. 73(S1), pages 26-30, March.
    4. Andrew Delios, 2017. "The Death and Rebirth (?) of International Business Research," Journal of Management Studies, Wiley Blackwell, vol. 54(3), pages 391-397, May.
    5. Valentin Amrhein & David Trafimow & Sander Greenland, 2019. "Inferential Statistics as Descriptive Statistics: There Is No Replication Crisis if We Don’t Expect Replication," The American Statistician, Taylor & Francis Journals, vol. 73(S1), pages 262-270, March.
    6. Gelman, Andrew & Stern, Hal, 2006. "The Difference Between," The American Statistician, American Statistical Association, vol. 60, pages 328-331, November.
    7. Klaus E Meyer & Arjen Witteloostuijn & Sjoerd Beugelsdijk, 2017. "What’s in a p? Reassessing best practices for conducting and reporting hypothesis-testing research," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 48(5), pages 535-551, July.
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    Cited by:

    1. Donald Bergh, 2021. "Research methods in international business," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 52(6), pages 1225-1228, August.
    2. van Hugten, Joeri & Coreynen, Wim & Vanderstraeten, Johanna & van Witteloostuijn, Arjen, 2023. "The Dunning-Kruger effect and entrepreneurial self-efficacy: How tenure and search distance jointly direct entrepreneurial self-efficacy," Journal of Business Research, Elsevier, vol. 161(C).
    3. Bas Bosma & Arjen Witteloostuijn, 2024. "Machine learning in international business," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 55(6), pages 676-702, August.
    4. Luis Alfonso Dau & Grazia D. Santangelo & Arjen Witteloostuijn, 2022. "Replication studies in international business," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 53(2), pages 215-230, March.

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