Asymptotic distribution of ∆AUC, NRIs, and IDI based on theory of U-statistics.

ABSTRACT: The change in area under the curve (∆AUC), the integrated discrimination improvement (IDI), and net reclassification index (NRI) are commonly used measures of risk prediction model performance. Some authors have reported good validity of associated methods of estimating their standard errors (SE) and construction of confidence intervals, whereas others have questioned their performance. To address these issues, we unite the ∆AUC, IDI, and three versions of the NRI under the umbrella of the U-statistics family. We rigorously show that the asymptotic behavior of ∆AUC, NRIs, and IDI fits the asymptotic distribution theory developed for U-statistics. We prove that the ∆AUC, NRIs, and IDI are asymptotically normal, unless they compare nested models under the null hypothesis. In the latter case,

SUBMITTER: Demler OV 

PROVIDER: S-EPMC5931715 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature