Relaxing the Rule of Ten Events per Variable in Logistic and Cox Regression

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Original Contribution Relaxing the Rule of Ten Events per Variable in Logistic and Cox Regression

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...

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

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...

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A simulation study of the number of events per variable in logistic regression analysis.

We performed a Monte Carlo study to evaluate the effect of the number of events per variable (EPV) analyzed in logistic regression analysis. The simulations were based on data from a cardiac trial of 673 patients in which 252 deaths occurred and seven variables were cogent predictors of mortality; the number of events per predictive variable was (252/7 =) 36 for the full sample. For the simulat...

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No rationale for 1 variable per 10 events criterion for binary logistic regression analysis

BACKGROUND Ten events per variable (EPV) is a widely advocated minimal criterion for sample size considerations in logistic regression analysis. Of three previous simulation studies that examined this minimal EPV criterion only one supports the use of a minimum of 10 EPV. In this paper, we examine the reasons for substantial differences between these extensive simulation studies. METHODS The ...

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Cumulants and Bartlett Identities in Cox Regression by Per

Expressions are found for the cumulants needed to analyze Cox regression up to order O(n−3/2), and consistent estimators for these are given. In addition, the Bartlett identities are shown to hold for the Cox partial likelihood (and, in a broad sense, for partial likelihood in general), so that the cumulant estimators found can be used to adjust statistics in accordance with formulas from likel...

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ژورنال

عنوان ژورنال: American Journal of Epidemiology

سال: 2007

ISSN: 0002-9262,1476-6256

DOI: 10.1093/aje/kwk052