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Using The Roc Curve To Measure Association And Evaluate Prediction Accuracy For A Binary Outcome, Jingjing Yin, Robert L. Vogel

Biostatistics Faculty Publications

This review article addresses the ROC curve and its advantage over the odds ratio to measure the association between a continuous variable and a binary outcome. A simple parametric model under the normality assumption and the method of Box-Cox transformation for non-normal data are discussed. Applications of the binormal model and the Box-Cox transformation under both univariate and multivariate inference are illustrated by a comprehensive data analysis tutorial. Finally, a summary and recommendations are given as to the usage of the binormal ROC curve.