Nonparametric estimation of conditional ROC curves: application to discrimination tasks in computerized detection of early breast cancer. (English) Zbl 1452.62826
Summary: A local linear method for estimating the conditional ROC curve under the presence of continuous and categorical covariates is introduced. A data driven smoothing parameter selector based on the bootstrap is proposed. The methods are illustrated with real data from a discrimination problem emerging in the context of computer-aided diagnosis. The bootstrap approach is also used to construct pointwise confidence intervals for the area under the ROC curve.
MSC:
| 62P10 | Applications of statistics to biology and medical sciences; meta analysis |
| 62G07 | Density estimation |
| 62G09 | Nonparametric statistical resampling methods |
| 62G15 | Nonparametric tolerance and confidence regions |
| 62-08 | Computational methods for problems pertaining to statistics |
Keywords:
ROC curve; local linear estimator; smoothing; bootstrap; conditional distribution; bandwidth selection; microcalcifications; computer-aided diagnosisReferences:
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