• 1. Peng R. The reproducibility crisis in science: a statistical counterattack. Significance 2015;12:3032.

  • 2. Barba LA. The hard road to reproducibility. Science 2016;354:142.

  • 3. Munafo MR, Nosek BA, Bishop DVM, et al. A manifesto for reproducible science. Nat Hum Behav 2017;1:0021.

  • 4. Baker M. 1,500 scientists lift the lid on reproducibility. Nature 2016;533:452454.

  • 5. Collins FS, Tabak LA. Policy: NIH plans to enhance reproducibility. Nature 2014;505:612613.

  • 6. Begley CG. Six red flags for suspect work. Nature 2013; 497:433434.

  • 7. Perrin S. Preclinical research: make mouse studies work. Nature 2014;507:423425.

  • 8. Begley CG, Ellis LM. Drug development: raise standards for preclinical cancer research. Nature 2012;483:531533.

  • 9. Begley CG, Ioannidis JP. Reproducibility in science: improving the standard for basic and preclinical research. Circ Res 2015;116:116126.

    • Search Google Scholar
    • Export Citation
  • 10. Ioannidis JP. Why most published research findings are false. PLoS Med 2005;2:e124.

  • 11. Nuzzo R. Scientific method: statistical errors. Nature 2014;506:150152.

  • 12. Greenland S. Multiple comparisons and association selection in general epidemiology. Int J Epidemiol 2008;37:430434.

  • 13. Guller U, DeLong ER. Interpreting statistics in medical literature: a vade mecum for surgeons. J Am Coll Surg 2004;198:441458.

  • 14. Head ML, Holman L, Lanfear R, et al. The extent and consequences of p-hacking in science. PLoS Biol 2015;13:e1002106.

  • 15. Bender R, Lange S. Adjusting for multiple testing—when and how? J Clin Epidemiol 2001;54:343349.

  • 16. Kerr NL. HARKing: hypothesizing after the results are known. Pers Soc Psychol Rev 1998;2:196217.

  • 17. Delgado-Rodríguez M, Llorca J. Bias. J Epidemiol Community Health 2004;58:635641.

  • 18. Lanyon L. Evidence-based veterinary medicine: a clear and present challenge. Vet Rec 2014;174:173175.

  • 19. Vandeweerd JM, Kirschvink N, Clegg P, et al. Is evidence-based medicine so evident in veterinary research and practice? History, obstacles and perspectives. Vet J 2012;191:2834.

    • Search Google Scholar
    • Export Citation
  • 20. White BJ, Larson RL. Systematic evaluation of scientific research for clinical relevance and control of bias to improve clinical decision making. J Am Vet Med Assoc 2015;247:496500.

    • Search Google Scholar
    • Export Citation
  • 21. Kelsey JL. A contrary view on statistical significance. J Am Vet Med Assoc 2011;239:428429.

  • 22. West CP, Dupras DM. 5 ways statistics can fool you. Tips for practicing clinicians. Vaccine 2013;31:15501552.

  • 23. Mullin CM, Arkans MA, Sammarco CD, et al. Doxorubicin chemotherapy for presumptive cardiac hemangiosarcoma in dogs. Vet Comp Oncol 2016;14:e171e183.

    • Search Google Scholar
    • Export Citation
  • 24. Holtermann N, Kiupel M, Kessler M, et al. Masitinib monotherapy in canine epitheliotropic lymphoma. Vet Comp Oncol 2016;14(suppl 1):127135.

    • Search Google Scholar
    • Export Citation
  • 25. Lehmann EL. The Fisher, Neyman-Pearson theories of testing hypotheses: one theory or two? J Am Stat Assoc 1993;88:12421249.

  • 26. Sterne JA, Davey Smith G. Sifting the evidence-what's wrong with significance tests? BMJ 2001;322:226231.

  • 27. Jeffery N. Liberating the (data) population from subjugation to the 5% (P-value). J Small Anim Pract 2015;56:483484.

  • 28. McShane B, Gal D, Gelman A, et al. Abandon statistical significance. Am Stat 2019;73:235245.

  • 29. Amrhein V, Greenland S, McShane B. Scientists rise up against statistical significance. Nature 2019;567:305307.

  • 30. Grimes DA, Schulz KF. Uses and abuses of screening tests. Lancet 2002;359:881884.

  • 31. White BJ, Larson RL, Theurer ME. Interpreting statistics from published research to answer clinical and management questions. J Anim Sci 2016;94:49594971.

    • Search Google Scholar
    • Export Citation
  • 32. Browner WS, Newman TB. Are all significant P values created equal? The analogy between diagnostic tests and clinical research. JAMA 1987;257:24592463.

    • Search Google Scholar
    • Export Citation
  • 33. Greenland S. Bayesian perspectives for epidemiological research: I. Foundations and basic methods. Int J Epidemiol 2006;35:765775.

    • Search Google Scholar
    • Export Citation
  • 34. Lash TL. The harm done to reproducibility by the culture of null hypothesis significance testing. Am J Epidemiol 2017; 186:627635.

    • Search Google Scholar
    • Export Citation
  • 35. Wacholder S, Chanock S, Garcia-Closas M, et al. Assessing the probability that a positive report is false: an approach for molecular epidemiology studies. J Natl Cancer Inst 2004;96:434442.

    • Search Google Scholar
    • Export Citation
  • 36. Held L. Reverse-Bayes analysis of two common misinterpretations of significance tests. Clin Trials 2013;10:236242.

  • 37. Goodman SN. P values, hypothesis tests, and likelihood: implications for epidemiology of a neglected historical debate. Am J Epidemiol 1993;137:485496, discussion 497–501.

    • Search Google Scholar
    • Export Citation
  • 38. Gliner JA, Leech NL, Morgan GA. Problems with null hypothesis significance testing (NHST): what do the textbooks say? J Exp Educ 2002;71:8392.

    • Search Google Scholar
    • Export Citation
  • 39. Greenland S, Senn SJ, Rothman KJ, et al. Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. Eur J Epidemiol 2016;31:337350.

    • Search Google Scholar
    • Export Citation
  • 40. Goodman S. A dirty dozen: twelve p-value misconceptions. Semin Hematol 2008;45:135140.

  • 41. Wasserstein RL, Lazar NA. The ASA's statement on p-values: context, process, and purpose. Am Stat 2016;70:129133.

  • 42. Wagenmakers EJ. A practical solution to the pervasive problems of P values. Psychon Bull Rev 2007;14:779804.

  • 43. Benjamin DJ, Berger JO, Johannesson M, et al. Redefine statistical significance. Nat Hum Behav 2018;2:610.

  • 44. Trafimow D, Amrhein V, Areshenkoff CN, et al. Manipulating the alpha level cannot cure significance testing. Front Psychol 2018;9:699.

  • 45. Altman DG, Bland JM. Diagnostic tests 2: predictive values. BMJ 1994;309:102.

  • 46. Matthews RAJ. Why should clinicians care about Bayesian methods? J Stat Plan Inference 2001;94:4358.

  • 47. Colquhoun D. The reproducibility of research and the misinterpretation of p-values (Erratum published in R Soc Open Sci 2018;5:180100). R Soc Open Sci 2017;4:171085.

    • Search Google Scholar
    • Export Citation
  • 48. Ten Hagen KG. Novel or reproducible: that is the question. Glycobiology 2016;26:429.

  • 49. Mogil JS, Macleod MR. No publication without confirmation. Nature 2017;542:409411.

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Enhancing Clinical Decision-Making: Challenges of making decisions on the basis of significant statistical associations

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  • 1 1Biostatistics and Clinical Epidemiology Service, Ecole Nationale Vétérinaire d'Alfort, and U955 Institut Mondor de Recherche Biomédicale, Institut National de la Santé et de la Recherche Médicale, Université Paris Est Créteil, Maisons-Alfort, F-94700, France.

Contributor Notes

Address correspondence to Dr. Desquilbet (loic.desquilbet@vet-alfort.fr).