Statistical Mistakes

Misuse of statistical inference in medical research

Statistical significance

  1. Altman DG, Bland JM. Statistics notes: Absence of evidence is not evidence of absence. Br Med J 1995;311:485.
  2. Austin PC, Manca A, Zwarenstein M, Juurlink DN, Stanbrook MB. Baseline comparisons in randomized controlled trials. J Clin Epidemiol 2010;63:940-942.
  3. Bender R, Lange S. Adjusting for multiple testing – When and how? J Clin Epidemiol 2001;54:343–349.
  4. Bender R, Lange S. Multiple test procedures other than Bonferroni’s deserve wider use. BMJ 1999;318:600.
  5. Dmitrienko A, D’Agostino R. Traditional multiplicity adjustment methods in clinical trials. Stat Med 2013;32:5172–5218 doi:10.1002/sim.5990.
  6. Goodman SN. Aligning statistical and scientific reasoning. Science 2016;352:1180-1181.
  7. Greenland S, Senn SJ, Rothman KJ, Carlin JB, Poole C, Goodman SN, Altman DG. Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. Eur J Epidemiol 2016;31:337-350.
  8. Ioannidis JPA. Why Most Published Research Findings Are False. PLoS Med 2005;8:e124.
  9. Ranstam J. Why the p-value culture is bad and confidence intervals a better alternative. Osteoarthritis Cartilage 2012 April 11.
  10. Ranstam J. Multiple p-values and Bonferroni correction. Osteoarthritis Cartilage. 2016 Jan 21.
  11. Roberts C, Torgerson DJ. Baseline imbalance in randomised controlled trials. BMJ 1999;319:185.
  12. Senn S. Testing for baseline imbalance in clinical trials. Stat Med 1994;13:1715-1726.
  13. Wasserstein RL, Lazar NA. The ASA’s statement on p-values: context, process, and purpose. The American Statistician 2016 doi: 10.1080/00031305.2016.1154108
  14. Wood J, Freemantle N, King M, Nazareth I. Trap of trends to statistical significance: likelihood of near significant P value becoming more significant with extra data. BMJ 2014;348:g2215.