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Why is Getting Rid of P-Values So Hard? Musings on Science and Statistics

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  • Steven N. Goodman

Abstract

The current concerns about reproducibility have focused attention on proper use of statistics across the sciences. This gives statisticians an extraordinary opportunity to change what are widely regarded as statistical practices detrimental to the cause of good science. However, how that should be done is enormously complex, made more difficult by the balkanization of research methods and statistical traditions across scientific subdisciplines. Working within those sciences while also allying with science reform movements—operating simultaneously on the micro and macro levels—are the key to making lasting change in applied science.

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  • 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.
    • Handle: RePEc:taf:amstat:v:73:y:2019:i:s1:p:26-30
    DOI: 10.1080/00031305.2018.1558111
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    Cited by:

    1. Eleni Verykouki & Christos T. Nakas, 2023. "Adaptations on the Use of p -Values for Statistical Inference: An Interpretation of Messages from Recent Public Discussions," Stats, MDPI, vol. 6(2), pages 1-13, April.
    2. Gunter, Ulrich & Önder, Irem & Smeral, Egon, 2019. "Scientific value of econometric tourism demand studies," Annals of Tourism Research, Elsevier, vol. 78(C), pages 1-1.
    3. Ching‐Hua Yeh & Stefan Hirsch, 2023. "A meta‐regression analysis on the willingness‐to‐pay for country‐of‐origin labelling," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(3), pages 719-743, September.
    4. Emilyane de Oliveira Santana Amaral & Sergio Roberto Peres Line, 2021. "Current use of effect size or confidence interval analyses in clinical and biomedical research," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(11), pages 9133-9145, November.
    5. Leonid Hanin, 2021. "Cavalier Use of Inferential Statistics Is a Major Source of False and Irreproducible Scientific Findings," Mathematics, MDPI, vol. 9(6), pages 1-13, March.
    6. 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.

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