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.
Original language | English |
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Pages (from-to) | 458-472 |
Number of pages | 15 |
Journal | Biometrical Journal |
Volume | 47 |
Issue number | 4 |
DOIs | |
State | Published - Aug 2005 |
Keywords
- Diagnostic markers
- Kernel smoothing
- Power transformation
- Sensitivity Specificity
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty