Comparison for the Classification and Prediction Accuracies of Continuous Markers
Date Issued
2010
Date
2010
Author(s)
Chiang, Chuan-Hsiang
Abstract
The receiver operating characteristic curves (ROC) and the positive predictive value (PPV) curve are often used to assess the performance of a continuous marker in classification and prediction, respectively. In this thesis, we showed that the better the marker in classification, the better the marker in prediction, and vice versa.
Moreover, some test rules were established based on a variety of coordinate systems and metric measurements for the closeness between the ROC curves and that for the PPV curves. A class of simulation experiments were further implemented to investigate the performances of the developed inference procedures. In addition, our
procedures are applied to two empirical examples from the studies of Pima-Indian diabetes and liver disorders.
Subjects
area between curve (ABC)
area under curve (AUC)
bootstrap
false positive rate (FPR)
nonparametric estimator
positive predictive value
receiver operating characteristic curve (ROC)
true positive rate (TPR)
U-statistic
SDGs
Type
thesis
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