Abstract
Cut-points selection is a key topic in the field of diagnostic studies. For binary classification, there exist several well-developed methods, some of which have been extended to three-class settings and beyond. This paper focuses on optimal cut-points selection methods for diseases with multiple ordinal stages. The purpose of this paper is two-fold: 1) to propose three new cut-points selection methods; and 2) to present a comprehensive simulation study to assess and compare the performance of all the available methods. Two real data sets, one from ovarian cancer and the other from pancreatic cancer, are analyzed.
| Original language | English |
|---|---|
| Pages (from-to) | 46-68 |
| Number of pages | 23 |
| Journal | Journal of Biopharmaceutical Statistics |
| Volume | 30 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2 2020 |
Keywords
- area under ROC curve
- ROC curve
- ROC surface
- volume under ROC surfac
- Youden index
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