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TITLE: Smoothed Jackknife Empirical Likelihood Inference for the Difference of ROC Curves
ABSTRACT:
For the comparison of two diagnostic markers at a flexible specificity, people apply the difference of two correlated receiver operating characteristic (ROC) curves to identify the diagnostic test with stronger discriminant ability. In this paper, we employ jackknife empirical likelihood (JEL) method to construct confidence intervals for the difference of two correlated continuous-scale ROC curves. Using the jackknife pseudo-sample, we can avoid estimating several nuisance variables which have to be estimated in existing methods. We prove that the smoothed jackknife empirical log likelihood ratio is asymptotically chi-squared distribution. Furthermore, the simulation studies in terms of coverage probability and average length of confidence intervals show the good performance in small samples with a moderate computational cost. A real data set is used to illustrated our method.
This is joint work with Dr. Hanfang Yang
