A non-parametric test for comparing conditional ROC curves

Arís Fanjul-Hevia, Wenceslao González-Manteiga and Juan Carlos Pardo-Fernández

Computational Statistics & Data Analysis, 2021, vol. 157, issue C

Abstract: Comparing the accuracy and the behaviour of different diagnostic procedures is one of the main objectives of the Receiver Operating Characteristic (ROC) curve analysis. Along with the diagnostic variables it is usual to observe other covariates, but that extra information has been hardly ever considered for the comparison of this kind of curves. A new non-parametric test is proposed for the comparison of conditional ROC curves. This test is based on a statistic whose theoretical properties are examined, and a bootstrap mechanism is used to calibrate the test. Simulations are run to analyse the practical performance of the test in terms of level approximation and power. An application to real data is also presented to illustrate the procedure.

Keywords: Bootstrap; Covariates; Hypothesis testing; ROC curves (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:157:y:2021:i:c:s0167947320302371

DOI: 10.1016/j.csda.2020.107146

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