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Relaxing the rule of ten events per variable in logistic and Cox regression.

American Journal of Epidemiology

Sensitivity and Specificity, Sample Size, Proportional Hazards Models, Prevalence, Predictive Value of Tests, Multivariate Analysis, Logistic Models, Humans, Factor Analysis, Statistical, Data Interpretation, Statistical, Confounding Factors (Epidemiology), Confidence Intervals, Case-Control Studies, Bias (Epidemiology)

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      The rule of thumb that logistic and Cox models should be used with a minimum of 10 outcome events per predictor variable (EPV), based on two simulation studies, may be too conservative. The authors conducted a large simulation study of other influences on confidence interval coverage, type I error, relative bias, and other model performance measures. They found a range of circumstances in which coverage and bias were within acceptable levels despite less than 10 EPV, as well as other factors that were as influential as or more influential than EPV. They conclude that this rule can be relaxed, in particular for sensitivity analyses undertaken to demonstrate adequate control of confounding.

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