Simulation study shows regression shrinkage improves average calibration of binary clinical models but raises between-sample variability and often applies the wrong amount of shrinkage in individual datasets.
Sample size for binary logistic prediction models: Beyond events per variable criteria No rationale for 1 variable per 10 events criterion for binary logistic regression analysis
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On the variability of regression shrinkage methods for clinical prediction models: simulation study on predictive performance
Simulation study shows regression shrinkage improves average calibration of binary clinical models but raises between-sample variability and often applies the wrong amount of shrinkage in individual datasets.