Estimation of the Youden Index and its Associated Cutoff Point

2005/08/01 by Ronen Fluss, David Faraggi, Benjamin Reiser · 7 citations
Decision Sciences · Mathematics · #Advanced Statistical Process Monitoring #Statistical Methods and Inference #Statistical Methods in Clinical Trials

paper · doi:10.1002/bimj.200410135

openalex publication_date 2005/08/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31

Abstract

The Youden Index is a frequently used summary measure of the ROC (Receiver Operating Characteristic) curve. It both, measures the effectiveness of a diagnostic marker and enables the selection of an optimal threshold value (cutoff point) for the marker. In this paper we compare several estimation procedures for the Youden Index and its associated cutoff point. These are based on (1) normal assumptions; (2) transformations to normality; (3) the empirical distribution function; (4) kernel smoothing. These are compared in terms of bias and root mean square error in a large variety of scenarios by means of an extensive simulation study. We find that the empirical method which is the most commonly used has the overall worst performance. In the estimation of the Youden Index the kernel is generally the best unless the data can be well transformed to achieve normality whereas in estimation of the optimal threshold value results are more variable.

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