Journal
BIOMETRICS
Volume 67, Issue 2, Pages 568-576Publisher
WILEY-BLACKWELL
DOI: 10.1111/j.1541-0420.2010.01450.x
Keywords
Cross-validation; Over-fitting; ROC curve; Variable selection
Funding
- GSU
- NSF
Ask authors/readers for more resources
When several diagnostic tests are available, one can combine them to achieve better diagnostic accuracy. This article considers the optimal linear combination that maximizes the area under the receiver operating characteristic curve (AUC); the estimates of the combination's coefficients can be obtained via a nonparametric procedure. However, for estimating the AUC associated with the estimated coefficients, the apparent estimation by re-substitution is too optimistic. To adjust for the upward bias, several methods are proposed. Among them the cross-validation approach is especially advocated, and an approximated cross-validation is developed to reduce the computational cost. Furthermore, these proposed methods can be applied for variable selection to select important diagnostic tests. The proposed methods are examined through simulation studies and applications to three real examples.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available