Adequate sample size for developing prediction models is not simply related to events per variable
Top Cited Papers
Open Access
- 7 March 2016
- journal article
- research article
- Published by Elsevier BV in Journal of Clinical Epidemiology
- Vol. 76, 175-182
- https://doi.org/10.1016/j.jclinepi.2016.02.031
Abstract
No abstract availableKeywords
This publication has 18 references indexed in Scilit:
- Performance of logistic regression modeling: beyond the number of events per variable, the role of data structureJournal of Clinical Epidemiology, 2011
- Relaxing the Rule of Ten Events per Variable in Logistic and Cox RegressionAmerican Journal of Epidemiology, 2006
- The design of simulation studies in medical statisticsStatistics in Medicine, 2006
- Explained randomness in proportional hazards modelsStatistics in Medicine, 2004
- A new measure of prognostic separation in survival dataStatistics in Medicine, 2004
- A solution to the problem of separation in logistic regressionStatistics in Medicine, 2002
- Stepwise Selection in Small Data Sets A Simulation Study of Bias in Logistic Regression AnalysisJournal of Clinical Epidemiology, 1999
- Importance of events per independent variable in proportional hazards regression analysis II. Accuracy and precision of regression estimatesJournal of Clinical Epidemiology, 1995
- Bias reduction of maximum likelihood estimatesBiometrika, 1993
- On the existence of maximum likelihood estimates in logistic regression modelsBiometrika, 1984