The p-Value You Can’t Buy

American Statistician

Volumn 70, Issue 1, 2016, Pages 33-38

  Demidenko, Eugene ^a  

^a DARTMOUTH COLLEGE   (United States)

Author keywords

Discrimination error; Effect size; ROC curve; Significance testing

Indexed keywords

EID: 84962109384     PISSN: 00031305     EISSN: 15372731     Source Type: Journal    
DOI: 10.1080/00031305.2015.1069760     Document Type: Article

References (32)

1. J.Adler, (2014, May/June), “The Reformation,” Pacific Standard. Available at http://www.psmag.com/navigation/health-and-behavior/can-social-scientists-save-themselves-human-behavior-78858/
2. B.Alberts,, M.W.Kirschner,, S.Tilghman,, and H.Varmus, (2014), “Rescuing US Biomedical Research From Its Systemic Flaws,” PNAS, 111, 5773--5777.
3. S.J.Altschuler,, and L.F.Wu, (2010), “Cellular Heterogeneity: Do Differences Make a Difference?” Cell, 141, 559–563.
4. D.Bamber, (1975), “The Area Above the Ordinal Dominance Graph and the Area Below the Receiver Operating Characteristic Graph,” Journal of Mathematical Psychology, 12, 387–415.
5. R.H.Browne, (2010), “The t-Test p Value and Its Relationship to the Effect Size and P(X>Y),” The American Statistician, 64, 30–33.
6. J.Cohen, (1994), “The Earth is Round (p <.05),” American Psychologist, 49, 997–1003.
7. E.Demidenko, (2012), “Confidence Intervals and Bands for the Binormal ROC Curve Revisited,” Journal of Applied Statistics, 39, 67–79.
8. ——— (2013), Mixed Models: Theory and Applications with R (. 2nd ed.), Hoboken, NJ: Wiley.
9. E.Demidenko,, J.Sargent,, and T.Onega, (2012), “Random Effects Coefficient of Determination for Mixed and Meta-Analysis Models,” Communications in Statistics–Theory and Methods, 41, 953–969.
10. P.D.Ellis, (2010), The Essential Guide to Effect Sizes, Cambridge, UK: Cambridge University Press.
11. A.Field, (2005), Discovering Statistics Using SPSS, London: Sage.
12. A.Gelman, (2013), “Commentary: P Values and Statistical Practice,” Epidemiology, 24, 69–72.
13. A.Gelman,, and H.Stern, (2006), “The Difference Between ‘Significant’ and ‘Not Significant’ is Not Itself Statistically Significant,” The American Statistician, 60, 328–331.
14. S.Greenland,, and C.Poole, (2013), “Living With p Values: Resurrecting a Bayesian Perspective on Frequentist Statistics,” Epidemiology, 24, 62–68.
15. J.Gunawardena, (2014), “Models in Biology: Accurate Descriptions of Our Pathetic Thinking,” BMC Biology, 12, 29.
16. L.A.Harvey, (2014), “Statistical Power Calculations Reflect Our Love Affair With p-Values and Hypothesis Testing: Time for a Fundamental Change,” Spinal Cord, 52, 2–2.
17. V.E.Johnson, (2013), “Revised Standards for Statistical Evidence,” PNAS, 111, 5773–5777.
18. T.R.Joy,, A.Monjed,, G.Y.Zou,, R.A.Hegele,, H.G.McDonald,, and J.L.Mahon, (2014), “N-of-1 (single-Patient) Trials for Statin-Related Myalgia,” Annals of Internal Medicine, 60, 301–312.
19. E.O.Lillie,, B.Patay,, J.Diamant,, B.Issell,, E.J.Topol,, and N.J.Schork, (2011), “The n-of-1 Clinical Trial: The Ultimate Strategy for Individualizing Medicine?” Personalized Medicine, 8, 161–173.
20. C.E.Metz, (1978), “Basic Principles of ROC Analysis,” Seminars in Nuclear Medicine, 8, 283–298.
21. R.G.Newcombe, (2006a), “Confidence Intervals for an Effect Size Measure Based on the Mann–Whitney Statistic. Part 1: General Issues and Tail-Area-Based Methods,” Statistics in Medicine, 25, 543–557.
22. ——— (2006b), “Confidence Intervals for an Effect Size Measure Based on the Mann–Whitney Statistic. Part 2: Asymptotic Methods and Evaluation,” Statistics in Medicine, 25, 559–573.
23. R.Nuzzo, (2013), “Statistical Errors,” Nature, 506, 150–152.
24. T.Onega,, E.J.Duel,, X.Shi,, D.Wang,, E.Demidenko,, and D.Goodman, (2008), “Geographic Access to Cancer Care in the U.S,” Cancer, 138, 1919–1933.
25. P.Pharoah, (2007), “How Not to Interpret a p-Value?” Journal of the National Cancer Institute, 99, 332–333.
26. B.Rosner, (2011), Fundamentals of Biostatistics (7th ed.), Boston, MA: Brooks/Cole.
27. T.Siegfried, (2010), “Odds Are, It’s Wrong: Science Fails to Face the Shortcomings of Statistics,” Science News, 177, 26-31. Available at https://www.sciencenews.org/article/odds-are-its-wrong.
28. S.Sun,, W.Pan,, and L.L.Wang, (2010), “A Comprehensive Review of Effect Size Reporting and Interpreting Practices in Academic Journals in Education and Psychology,” Journal of Educational Psychology, 102, 989–1004.
29. Tarran, B. and Wininger, M.2015A Psychology Journal Bans P-values,” 126.
30. D.Trafimow,, and M.Marks, (2015), “Editorial,” Basic and Social Psychology, 37, 1–2.
31. D.A.Wolfe,, and R.V.Hogg, (1971), “On Constructing Statistics and Reporting Data,” American Statistician, 25, 27–30.
32. W.Zhou, (2008), “Statistical Inference for P(X < Y),” Statistics in Medicine, 27, 257–279.