Statistical Mistakes

The statistical reviewer's handbook

Parameter interpretation

  1. Barros AJD, Hirakata VN. Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio. BMC Med Res Method 2003, 3:21
  2. Coutinho LMS, Scazufca M, Menezes PR. Methods for estimating prevalence ratios in cross-sectional studies. Rev Saúde Pública 2008;42:1-6.
  3. Davies HTO. When can odds ratios mislead? BMJ 1998;316:989.
  4. Dignam JJ, Zhang Q, Kocherginsky MN. The Use and Interpretion of Competing Risks Regression Models. Clin Cancer Res 2012;18:2301–2308.
  5. Grant RL. Converting an odds ratio to a range of plausible relative risks for better communication of research findings. BMJ 2014;348:f7450
  6. Greenland S, Schlesselman JJ, Criqui, MH. The fallacy of employing standardized regression coefficients and correlations as measures of effect. Am J Epidemiol. 1986;123:203–208.
  7. McNutt L-A, Wu C, Xue X, Hafner JP. Estimating the Relative Risk in Cohort Studies and Clinical Trials of Common Outcomes. Am J Epidemiol 2003;157:940–943.
  8. Mittleman M. Generalizability of Case-Crossover and Other Case-only Designs in Environmental Epidemiology. Epidemiology 2006;17:S224.
  9. Rutherford MJ. Care needed in interpretation of cancer survival measures. Lancet 2015;385:1162-1163.
  10. Satagopan JM, Ben-Porat L, Berwick M, Robson M, Kutler D, Auerbach AD. A note on competing risks in survival data analysis. Br J Cancer 2004;91:1229-1235.
  11. Vittinghoff E, McCulloch CE. Relaxing the rule of ten events per variable in logistic and Cox regression. Am J Epidemiol 2007;165:710-718.
  12. Zhang J, Yu KF. What’s the Relative Risk? A Method of Correcting the Odds Ratio in Cohort Studies of Common Outcomes. JAMA 1998;280:1690-1691.
  13. Zhang Z. Case-crossover design and its implementation in R. Ann Transl Med. 2016 Sep; 4(18): 341.


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