Improving Calibration of Logistic Regression Models by Local Estimates

Abstract

OBJECTIVE To improve the calibration of logistic regression (LR) estimates using local information. BACKGROUND Individualized risk assessment tools are increasingly being utilized. External validation of these tools often reveals poor model calibration. METHODS We combine a clustering algorithm with an LR model to produce probability estimates that are… (More)

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