Abstract
The calibration belt is a graphical approach designed to evaluate the goodness of
fit of binary outcome models such as logistic regression models. The calibration
belt examines the relationship between estimated probabilities and observed
outcome rates. Significant deviations from the perfect calibration can be
spotted on the graph. The graphical approach is paired to a statistical test,
synthesizing the calibration assessment in a standard hypothesis testing
framework. In this article, we present the