Abstract
Comparison of two samples can sometimes be conducted on the basis of analysis of ROC curves. A variety of methods of point estimation and confidence intervals for ROC curves have been proposed and studied well. We develop smoothed empirical likelihood based confidence intervals for ROC curves when the samples are censored and generated from semiparametric models. The resulting empirical log-likelihood function is shown to be asymptotically chi-squared. Simulation studies illustrate that the proposed empirical likelihood confidence interval is advantageous over the normal approximation based confidence interval. A real data set is analyzed using the proposed method.
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