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Impact of redefining statistical significance on P-hacking and false positive rates: An agent-based model

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  • Ben G Fitzpatrick
  • Dennis M Gorman
  • Caitlin Trombatore

Abstract

In recent years, concern has grown about the inappropriate application and interpretation of P values, especially the use of P

Suggested Citation

  • Ben G Fitzpatrick & Dennis M Gorman & Caitlin Trombatore, 2024. "Impact of redefining statistical significance on P-hacking and false positive rates: An agent-based model," PLOS ONE, Public Library of Science, vol. 19(5), pages 1-18, May.
    • Handle: RePEc:plo:pone00:0303262
    DOI: 10.1371/journal.pone.0303262
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    References listed on IDEAS

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    1. Daniele Fanelli, 2010. "“Positive” Results Increase Down the Hierarchy of the Sciences," PLOS ONE, Public Library of Science, vol. 5(4), pages 1-10, April.
    2. Alexander J. Stewart & Joshua B. Plotkin, 2021. "The natural selection of good science," Nature Human Behaviour, Nature, vol. 5(11), pages 1510-1518, November.
    3. Christopher D. Chambers & Loukia Tzavella, 2022. "The past, present and future of Registered Reports," Nature Human Behaviour, Nature, vol. 6(1), pages 29-42, January.
    4. Christopher Allen & David M A Mehler, 2019. "Open science challenges, benefits and tips in early career and beyond," PLOS Biology, Public Library of Science, vol. 17(5), pages 1-14, May.
    5. repec:plo:pbio00:3000587 is not listed on IDEAS
    6. 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.
    7. Robert MacCoun & Saul Perlmutter, 2015. "Blind analysis: Hide results to seek the truth," Nature, Nature, vol. 526(7572), pages 187-189, October.
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