Assessing the Calibration of Dichotomous Outcome Models with the Calibration Belt

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 calibrationbelt command, which implements the calibration belt and its associated test in Stata.