Abstract
The area under the receiver operating characteristic curve (overall C) is a widely used measure of a prognostic model discrimination. In this paper, we develop a nonparametric test for the comparison of two correlated C indexes of two different models when applied to the same population. We extend the DeLong's approach and use the theory of the jackknife methodology applied to correlated one sample generalized U-statistics. We derive the distribution of correlated estimators of C indexes as well as a consistent estimate of the asymptotic variance, leading to an asymptotically normal test.
Keywords
Jackknife resamplingNonparametric statisticsEstimatorStatisticsMathematicsAsymptotic distributionDelta methodEconometricsInferenceVariance (accounting)Statistical inferenceAsymptotic analysisPopulationNormal distributionApplied mathematicsComputer scienceMedicineArtificial intelligenceEconomics
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Publication Info
- Year
- 2004
- Type
- article
- Volume
- 33
- Issue
- 9
- Pages
- 2117-2135
- Citations
- 71
- Access
- Closed
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Cite This
Laura Antolini,
Byung‐Ho Nam,
Ralph B. D’Agostino
(2004).
Inference on Correlated Discrimination Measures in Survival Analysis: A Nonparametric Approach.
Communication in Statistics- Theory and Methods
, 33
(9)
, 2117-2135.
https://doi.org/10.1081/sta-200026579
Identifiers
- DOI
- 10.1081/sta-200026579