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The p-Value Requires Context, Not a Threshold

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  • Rebecca A. Betensky

Abstract

It is widely recognized by statisticians, though not as widely by other researchers, that the p-value cannot be interpreted in isolation, but rather must be considered in the context of certain features of the design and substantive application, such as sample size and meaningful effect size. I consider the setting of the normal mean and highlight the information contained in the p-value in conjunction with the sample size and meaningful effect size. The p-value and sample size jointly yield 95% confidence bounds for the effect of interest, which can be compared to the predetermined meaningful effect size to make inferences about the true effect. I provide simple examples to demonstrate that although the p-value is calculated under the null hypothesis, and thus seemingly may be divorced from the features of the study from which it arises, its interpretation as a measure of evidence requires its contextualization within the study. This implies that any proposal for improved use of the p-value as a measure of the strength of evidence cannot simply be a change to the threshold for significance.

Suggested Citation

  • Rebecca A. Betensky, 2019. "The p-Value Requires Context, Not a Threshold," The American Statistician, Taylor & Francis Journals, vol. 73(S1), pages 115-117, March.
    • Handle: RePEc:taf:amstat:v:73:y:2019:i:s1:p:115-117
    DOI: 10.1080/00031305.2018.1529624
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    Cited by:

    1. Palea, Vera & Drogo, Federico, 2020. "Carbon Emissions and the Cost of Debt Financing: What Role for Policy Commitment, Firm Disclosure and Corporate Governance?," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202002, University of Turin.
    2. Pütz, Peter & Kramer-Sunderbrink, Arne & Dreher, Robin Tim & Hoffmann, Leona & Werner, Robin, 2022. "A Proposed Hybrid Effect Size Plus p-Value Criterion. A Comment on Goodman et al. (The American Statistician, 2019)," Journal of Comments and Replications in Economics (JCRE), ZBW - Leibniz Information Centre for Economics, vol. 1(2022-4), pages 1-15.
    3. Andrea Ongaro & Sonia Migliorati & Roberto Ascari & Enrico Ripamonti, 2024. "Testing practical relevance of treatment effects," Statistical Papers, Springer, vol. 65(7), pages 4121-4145, September.
    4. Young-Ju Song & Kyung-Su Oh & Beom Lee & Dae-Won Pak & Ji-Hwan Cha & Jun-Gyu Park, 2021. "Characteristics of Biogas Production from Organic Wastes Mixed at Optimal Ratios in an Anaerobic Co-Digestion Reactor," Energies, MDPI, vol. 14(20), pages 1-16, October.
    5. Jae H. Kim, 2022. "Moving to a world beyond p-value," Review of Managerial Science, Springer, vol. 16(8), pages 2467-2493, November.
    6. Oliver Gutiérrez-Hernández & Luis Ventura García, 2021. "Multiplicity Eludes Peer Review: The Case of COVID-19 Research," IJERPH, MDPI, vol. 18(17), pages 1-10, September.
    7. Marica Barbaritano & Elisabetta Savelli, 2021. "How Consumer Environmental Responsibility Affects the Purchasing Intention of Design Furniture Products," Sustainability, MDPI, vol. 13(11), pages 1-18, May.

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