2017•Journal of Biopharmaceutical StatisticsRequires access

Novel tests for evaluating two ROC curves under paired samples

Yi‐Ting Hwang, Chun‐Chao Wang

Open publisher page 2 citations

Abstract

Disease prevention is important and can be accomplished by developing diagnostic tests. The receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) are used to assess the accuracy of diagnostic tests. The assessment for the superiority between evaluating two diagnostic tests is needed when comparing two diagnostic tests. Existing tests are constructed by comparing two AUCs under the paired samples. Nevertheless, it is problematic when two ROC curves are crossing. This article proposes a test that takes into account the possible correlation between pairs. Simulations are conducted to evaluate the feasibility of the test.

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What this paper is about

Disease prevention is important and can be accomplished by developing diagnostic tests. The receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) are used to assess the accuracy of diagnostic tests. The assessment for the superiority between evaluating two diagnostic tests is needed when comparing two diagnostic tests. Existing tests are constructed by comparing two AUCs under the paired samples. Nevertheless, it is problematic when two ROC curves are crossing. This article proposes a test that takes into account the possible correlation between pairs. Simulations are conducted to evaluate the feasibility of the test.

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OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Disease prevention is important and can be accomplished by developing diagnostic tests. The receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) are used to assess the accuracy of diagnostic tests. The assessment for the superiority between evaluating two diagnostic tests is needed when comparing two diagnostic tests. Existing tests are constructed by comparing two AUCs under the paired samples. Nevertheless, it is problematic when two ROC curves are crossing. This article proposes a test that takes into account the possible correlation between pairs. Simulations are conducted to evaluate the feasibility of the test.

Key concepts: Receiver operating characteristic, Diagnostic test, Statistics, Diagnostic accuracy, Mathematics, Area under curve, Test (biology), Medicine

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