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Overall <i>C</i> as a measure of discrimination in survival analysis: model specific population value and confidence interval estimation

Statistics in Medicine · 2004 · Vol. 23(13) · pp. 2109–2123

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 tau and 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.

Statistical Methods and Bayesian InferenceStatistical Methods and InferenceStatistical Methods in Clinical TrialsStatisticsConfidence intervalStatisticLogistic regressionMeasure (data warehouse)PopulationNormalityEconometricsInterval (graph theory)Asymptotic distribution

MeSH terms

HawaiiHeart DiseasesHumansMaleROC CurveCohort StudiesConfidence IntervalsSurvival Analysis
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