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The area under a ROC curve (AUC) and the partial area under a ROC curve (pAUC) are two important summary measures for assessing the accuracy of a diagnostic test discriminating a binary true disease status. We develop nonparametric estimation of AUC and pAUC under a biased sampling scheme in which a random sample is supplemented with a test-result-dependent sample. Such biased sampling scheme can arise from an existing study with sampling limitation or a study under development for better estimation efficiency.
