Assessing the calibration of dichotomous outcome models with the calibration belt

Giovanni Nattino (), Stanley Lemeshow, Gary Phillips, Stefano Finazzi and Guido Bertolini
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Giovanni Nattino: The Ohio State University
Stanley Lemeshow: The Ohio State University
Gary Phillips: The Ohio State University
Stefano Finazzi: IRCCS Istituto di Ricerche Farmacologiche ‘Mario Negri’
Guido Bertolini: IRCCS Istituto di Ricerche Farmacologiche ‘Mario Negri’

Stata Journal, 2017, vol. 17, issue 4, 1003-1014

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 ob- served outcome rates. Significant deviations from the perfect calibration can be spotted on the graph. The graphical approach is paired to a statistical test, syn- thesizing 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. Copyright 2017 by StataCorp LP.

Keywords: calibrationbelt; logistic regression; calibration; goodness of fit; binary outcome (search for similar items in EconPapers)
Date: 2017
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