Problems with P-Values

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Problems with p-values By Hedibert Lopes [email protected] hedibert.org February 2020 Text in red are downloadable 1. Why Most Published Research Findings Are False Ioannidis (2005) PLoS Medicine, 2(8), e124. 2. The Cult of Statistical Significance: How the Standard Error CostsUs Jobs, Justice, and Lives Ziliak and McCloskey (2008) University of Michigan Press, Ann Arbor, MI. 3. Revised Standards for Statistical Evidence Johnson (2013) Proceedings of the National Academy of Science, 110(48), 19313-19317. 4. Scientific method: Statistical errors Nuzzo (2014) Nature, 506, 150-152. 5. Estimating the reproducibility of psychological science Open Science Collaboration Science 349, (2015). 6. Not Even Scientists Can Easily Explain P-values Aschwanden (2015) 7. The ASA's Statement on p-Values: Context, Process, and Purpose Wasserstein and Lazar (2016) The American Statistician, 70(2), 129-133. 8. Statistical Tests, P-values, Confidence Intervals, and Power: A Guide to Misinterpretations Greenland, Senn, Rothman, Carlin, Poole, Goodman and Altman (2016) European Journal Epidemiology, 31, 337-350. 9. Statisticians Found One Thing They Can Agree On: It's Time To Stop Misusing P-Values Aschwanden (2016) 10. An investigation of the false discovery rate and the misinterpretation of p-values Colquhoun (2016) Royal Society of Open Science, 1, 140216. 1 11. The problem with p-values Colquhoun (2016) 12. Empirical assessment of published effect sizes and power in the recent cognitive neuroscience and psychology literature Szucs and Ioannidis (2016) PLoS Biololgy, 15(3), e2000797. 13. On the reproducibility of psychological science Johnson, Payne, Wang, Asher and Mandal (2017) Journal of the American Statistical Association, 112(517), 1-10. 14. Redefine Statistical Significance Benjamin, Berger, Johannesson et al (2018) Nature Human Behavior, 2, 6-10. 15. Retiring significance: raise the bar Johnson (2019) Nature, 567, 461. 16. Scientists rise up against statistical significance Valentin Amrhein, Sander Greenland, Blake McShane et al (2019) Nature, 567, 305-307. 17. Evidence from marginally significant t statistics Johnson (2019) The American Statistician, 73(S1), 129-134. 2.

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