P-value

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A p value is a value calculated from a research study, which is intended to show whether an outcome is likely to have occurred by chance, when taking into consideration a number of other factors.[1][2] P values are not actually defined as a probability.[3] P-hacking is the manipulation of research data to produce a clinically significant result for the calculated p value; meaning manipulating research results in order to achieve p < 0.05 rather than publishing a null result.[citation needed]

Theory[edit | edit source]

Evidence[edit | edit source]

Null hypothesis significance testing[edit | edit source]

Articles and blogs[edit | edit source]

Notable studies[edit | edit source]

  • 2012, A peculiar prevalence of p values just below .05[4] (Abstract)
  • 2013, The life of p: “Just significant” results are on the rise[5] (Abstract)
  • 2015, Blinded by the Light: How a Focus on Statistical “Significance” May Cause p-Value Misreporting and an Excess of p-Values Just Below .05 in Communication Science[7] (Full text)
  • 2016, Degrees of Freedom in Planning, Running, Analyzing, and Reporting Psychological Studies: A Checklist to Avoid p-Hacking[8] (Full text)

See also[edit | edit source]

Learn more[edit | edit source]

References[edit | edit source]

  1. "Miller-Keane Encyclopedia and Dictionary of Medicine, Nursing, and Allied Health". TheFreeDictionary.com (7th ed.). 2003. Retrieved Apr 21, 2019. 
  2. Merrian-Webster Dictionary. "Definition of P VALUE". www.merriam-webster.com. Retrieved Apr 21, 2019. 
  3. 3.0 3.1 Kuffner, Todd A.; Walker, Stephen G. (Jan 2, 2019). "Why are p-Values Controversial?". The American Statistician. 73 (1): 1–3. doi:10.1080/00031305.2016.1277161. ISSN 0003-1305. 
  4. Masicampo, E.J.; Lalande, Daniel R. (Nov 2012). "A peculiar prevalence of p values just below .05". Quarterly Journal of Experimental Psychology. 65 (11): 2271–2279. doi:10.1080/17470218.2012.711335. ISSN 1747-0218. 
  5. Leggett, Nathan C.; Thomas, Nicole A.; Loetscher, Tobias; Nicholls, Michael E. R. (Dec 1, 2013). "The life of p: "Just significant" results are on the rise". The Quarterly Journal of Experimental Psychology. 66 (12): 2303–2309. doi:10.1080/17470218.2013.863371. ISSN 1747-0218. PMID 24205936. 
  6. Lakens, Daniël (Apr 1, 2015). "Comment: What p-hacking really looks like: A comment on Masicampo and LaLande (2012)". Quarterly Journal of Experimental Psychology. 68 (4): 829–832. doi:10.1080/17470218.2014.982664. ISSN 1747-0218. 
  7. Vermeulen, Ivar; Beukeboom, Camiel J.; Batenburg, Anika; Avramiea, Arthur; Stoyanov, Dimo; van de Velde, Bob; Oegema, Dirk (Oct 2, 2015). "Blinded by the Light: How a Focus on Statistical "Significance" May Cause p-Value Misreporting and an Excess of p-Values Just Below .05 in Communication Science". Communication Methods and Measures. 9 (4): 253–279. doi:10.1080/19312458.2015.1096333. ISSN 1931-2458. 
  8. van Assen, Marcel A. L. M.; van Aert, Robbie C. M.; Bakker, Marjan; Augusteijn, Hilde E. M.; Veldkamp, Coosje L. S.; Wicherts, Jelte M. (2016). "Degrees of Freedom in Planning, Running, Analyzing, and Reporting Psychological Studies: A Checklist to Avoid p-Hacking". Frontiers in Psychology. 7. doi:10.3389/fpsyg.2016.01832. ISSN 1664-1078. 

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