Abstract
Abstract The assessment of the discrimination ability of a survival analysis model is a problem of considerable theoretical interest and important practical applications. This issue is, however, more complex than evaluating the performance of a linear or logistic regression. Several different measures have been proposed in the biostatistical literature. In this paper we investigate the properties of the overall C index introduced by Harrell as a natural extension of the ROC curve area to survival analysis. We develop the overall C index as a parameter describing the performance of a given model applied to the population under consideration and discuss the statistic used as its sample estimate. We discover a relationship between the overall C and the modified Kendall's τand construct a confidence interval for our measure based on the asymptotic normality of its estimate. Then we investigate via simulations the length and coverage probability of this interval. Finally, we present a real life example evaluating the performance of a Framingham Heart Study model. Copyright © 2004 John Wiley & Sons, Ltd.
Keywords
StatisticsConfidence intervalStatisticLogistic regressionMeasure (data warehouse)PopulationNormalityEconometricsInterval (graph theory)Asymptotic distributionMathematicsComputer scienceIndex (typography)Data miningEstimatorMedicine
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Publication Info
- Year
- 2004
- Type
- article
- Volume
- 23
- Issue
- 13
- Pages
- 2109-2123
- Citations
- 1423
- Access
- Closed
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Cite This
Michael Pencina,
Ralph B. D’Agostino
(2004).
Overall <i>C</i> as a measure of discrimination in survival analysis: model specific population value and confidence interval estimation.
Statistics in Medicine
, 23
(13)
, 2109-2123.
https://doi.org/10.1002/sim.1802
Identifiers
- DOI
- 10.1002/sim.1802