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Activity Number: 127
Type: Contributed
Date/Time: Monday, July 30, 2012 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Consulting
Abstract - #304842
Title: Classification Accuracy and Cut-Point Selection
Author(s): Xinhua Liu*+
Companies: Columbia University
Address: Department of Biostatistics, New York, NY, 10032, United States
Keywords: Classification accuracy ; Concordance probability ; Cut point ; Sensitivity ; Specificity

In biomedical research and practice, quantitative tests or biomarkers are often used for diagnostic or screening purposes, with a cut point established on the quantitative measurement to aid binary classification. We introduce an alternative to the traditional methods based on the Youden index and the closest-to-(0, 1) criterion for threshold selection. A concordance probability evaluating the classification accuracy of a dichotomized measure is defined as an objective function of the possible cut point. A non-parametric approach is used to search for the optimal cut point maximizing the objective function. The procedure is shown to perform well in a simulation study. Using data from a real-world study of arsenic-induced skin lesions, we apply the method to a measure of blood arsenic levels, selecting a cut point to be used as a warning threshold.

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