IDEAS home Printed from https://ideas.repec.org/a/abf/journl/v6y2018i3p001-009.html

What p-value must be used as the Statistical Significance Threshold? P

Author

Listed:
  • Bruno Mario Cesana

    (Former: Department of Molecular and Transactional Medicine, Statistics and Biomathematics Unit, Faculty of Medicine and Surgery, University of Brescia, Brescia, Italy; Contract Professor: Department of Clinical Sciences and Community Health, Unit of Medical Statistics, Biometry and Bioinformatics “Giulio A. Maccacaro†, Faculty of Medicine and Surgery, University of Milan, Milan, Italy)

Abstract

Statistical significance is a tool for making decisions on a probabilistic basis extensively used in the scientific world. It must be recognized that the 0.05 value as the threshold of the statistical significance is undoubtedly arbitrary and nothing prevents it from being modified according to well-founded arguments. Furthermore, it must also be recognized that the logic of the statistical significance test is quite debatable, as well as being little understood by researchers who are the main users. Also the meaning of p-values is often ignored with consequent misinterpretations and misunderstandings. I will give a general overview and some insights on the topics of the p-values and of the statistical significance.

Suggested Citation

  • Bruno Mario Cesana, 2018. "What p-value must be used as the Statistical Significance Threshold? P," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 6(3), pages 001-009, July.
    • Handle: RePEc:abf:journl:v:6:y:2018:i:3:p:001-009
    DOI: 10.26717/BJSTR.2018.06.001359
    as

    Download full text from publisher

    File URL: https://biomedres.us/pdfs/BJSTR.MS.ID.001359.pdf
    Download Restriction: no
    File URL: https://biomedres.us/fulltexts/BJSTR.MS.ID.001359.php
    Download Restriction: no
    File URL: https://libkey.io/10.26717/BJSTR.2018.06.001359?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Steven Goodman & Sander Greenland, 2007. "Why Most Published Research Findings Are False: Problems in the Analysis," PLOS Medicine, Public Library of Science, vol. 4(4), pages 1-1, April.
    2. Daniel J. Benjamin & James O. Berger & Magnus Johannesson & Brian A. Nosek & E.-J. Wagenmakers & Richard Berk & Kenneth A. Bollen & Björn Brembs & Lawrence Brown & Colin Camerer & David Cesarini & Chr, 2018. "Redefine statistical significance," Nature Human Behaviour, Nature, vol. 2(1), pages 6-10, January.
      • Daniel Benjamin & James Berger & Magnus Johannesson & Brian Nosek & E. Wagenmakers & Richard Berk & Kenneth Bollen & Bjorn Brembs & Lawrence Brown & Colin Camerer & David Cesarini & Christopher Chambe, 2017. "Redefine Statistical Significance," Artefactual Field Experiments 00612, The Field Experiments Website.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. José Miguel Molina Fernández & Rodrigo Gonzáles Zuazo, 2018. "Exposición al comercio internacional e ingresos laborales en Bolivia: evidencia al nivel del trabajador," Revista Latinoamericana de Desarrollo Economico, Carrera de Economía de la Universidad Católica Boliviana (UCB), issue 31, pages 10-31.
    2. Merl, Robert & Stöckl, Thomas & Palan, Stefan, 2023. "Insider trading regulation and shorting constraints. Evaluating the joint effects of two market interventions," Journal of Banking & Finance, Elsevier, vol. 154(C).
    3. Imai, Taisuke & Toussaert, Séverine & Baillon, Aurélien & Dreber, Anna & Ertaç, Seda & Johannesson, Magnus & Neyse, Levent & Villeval, Marie Claire, 2025. "Pre-Registration and Pre-Analysis Plans in Experimental Economics," I4R Discussion Paper Series 220, The Institute for Replication (I4R).
    4. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2019. "Return spillovers around the globe: A network approach," Economic Modelling, Elsevier, vol. 77(C), pages 133-146.
    5. Mayo, Deborah, 2024. "Error statistics, Bayes-factor Tests and the Fallacy of Non-exhaustive Alternatives," OSF Preprints tmgqd, Center for Open Science.
    6. Bernhard Voelkl & Lucile Vogt & Emily S Sena & Hanno Würbel, 2018. "Reproducibility of preclinical animal research improves with heterogeneity of study samples," PLOS Biology, Public Library of Science, vol. 16(2), pages 1-13, February.
    7. Dreber, Anna & Heikensten, Emma & Säve-Söderbergh, Jenny, 2022. "Why do women ask for less?," Labour Economics, Elsevier, vol. 78(C).
    8. Brenøe, Anne Ardila & Eyibak, Zeynep & Heursen, Lea & Ranehill, Eva & Weber, Roberto A., 2024. "Gender Identity and Economic Decision Making," IZA Discussion Papers 17564, IZA Network @ LISER.
    9. Owusu Victor Kwarteng & Gregar Ales & Ntsiful Alex, 2021. "Organizational diversity and competency-based performance: The mediating role of employee commitment and job satisfaction," Management & Marketing, Sciendo, vol. 16(4), pages 352-369, December.
    10. 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, pages 1-15.
    11. Valérie Orozco & Christophe Bontemps & Élise Maigné & Virginie Piguet & Annie Hofstetter & Anne Marie Lacroix & Fabrice Levert & Jean-Marc Rousselle, 2017. "How to make a pie? Reproducible Research for Empirical Economics & Econometrics," Post-Print hal-01939942, HAL.
    12. Barbieri, Nicolò & Marzucchi, Alberto & Rizzo, Ugo, 2020. "Knowledge sources and impacts on subsequent inventions: Do green technologies differ from non-green ones?," Research Policy, Elsevier, vol. 49(2).
    13. Buchanan, Erin Michelle & Scofield, John E., 2017. "Bulletproof Bias? Considering the Type of Data in Common Proportion of Variance Effect Sizes," OSF Preprints cs4vy, Center for Open Science.
    14. 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.
    15. Guillaume Coqueret, 2023. "Forking paths in financial economics," Papers 2401.08606, arXiv.org.
    16. Wan, Shuaibin & Liang, Xiongwei & Jiang, Haoran & Sun, Jing & Djilali, Ned & Zhao, Tianshou, 2021. "A coupled machine learning and genetic algorithm approach to the design of porous electrodes for redox flow batteries," Applied Energy, Elsevier, vol. 298(C).
    17. Lackner, Mario & Sonnabend, Hendrik, 2021. "Coping with advantageous inequity—Field evidence from professional penalty kicking," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 91(C).
    18. Kellner, Ralf & Rösch, Daniel, 2021. "A Bayesian Re-Interpretation of “significant” empirical financial research," Finance Research Letters, Elsevier, vol. 38(C).
    19. Jesper W. Schneider, 2015. "Null hypothesis significance tests. A mix-up of two different theories: the basis for widespread confusion and numerous misinterpretations," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 411-432, January.
    20. Raaj Kishore Biswas & Enamul Kabir & Hafiz T. A. Khan, 2019. "Causes of Urban Migration in Bangladesh: Evidence from the Urban Health Survey," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 38(4), pages 593-614, August.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:abf:journl:v:6:y:2018:i:3:p:001-009. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Angela Roy (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.