Abstract
ROC curve is a graphical representation of the relationship between sensitivity and specificity of a diagnostic test. It is a popular tool for evaluating and comparing different diagnostic tests in medical sciences. In the literature, the ROC curve is often estimated empirically based on an empirical distribution function estimator and an empirical quantile function estimator. In this paper an alternative nonparametric procedure to estimate the ROC curve is suggested which is based on local smoothing techniques. Several numerical examples are presented to evaluate the performance of this procedure.
Original language | English (US) |
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Pages (from-to) | 55-69 |
Number of pages | 15 |
Journal | Journal of Statistical Computation and Simulation |
Volume | 70 |
Issue number | 1 |
DOIs | |
State | Published - 2001 |
Keywords
- Diagnostic tests
- Empirical estimators
- Incomplete beta function
- Kernel distribution function estimator
- Quantile estimators
- ROC curves