A ROC-based test for evaluating the group difference with an application to neonatal audiology screening.
This article proposes a powerful method to compare two samples. The proposed method handles comparison of data by drawing inference from ROC curve model parameters. The method estimates parameters from a linear model framework on the empirical sensitivities and specificities. The consistent ROC parameters are then used to give a more powerful test than existing methods in several situations. In addition, we present a comprehensive statistic based on the Cauchy combination, which works well in all scenarios considered in this article. We also offer an efficient one-layer wild permutation procedure to calculate the P-value of our statistic. The method is particularly useful when the underlying continuous biomarker results are non-normal. We illustrate the proposed methods in a neonatal audiology diagnostic example.
['Tang|Larry L|LL|0000-0002-7276-155X', 'Meng|Zhen|Z|0000-0003-0337-422X', 'Li|Qizhai|Q|']
D001298:Audiology D006801:Humans D007231:Infant, Newborn D012372:ROC Curve D012680:Sensitivity and Specificity
ROC curve sensitivity specificity two-sample comparison