title: Nonparametric statistical inference method for partial areas under receiver operating characteristic curves, with application to genomic studies.
abstract: Recently ROC50 index-the area under the lower portion of the receiver operating characteristic (ROC) curve up to the first 50 false positives-has been increasingly widely used in genomic research. Unfortunately, statistical inferences on the ROC50 index are not commonly drawn due to a lack of handy statistical inference methods and/or software tools. In this paper, we reviewed developments in statistical methods for the partial areas under ROC curves and using nonparametric methods we derived a simple and direct variance calculation formula for the partial areas, different from existing methods in the literature. We have also verified our method through simulation studies and compared our method with existing bi-normal approaches. We have shown that the partial area has an asymptotic normal distribution using trimmed U-statistics theory. On the basis of this asymptotic normality, we have given formulas for the confidence interval and the test statistic and we reported on their application to a genomic study of sample size approximately 10,000.
authors.affiliation: Global Biometric Sciences, Bristol-Myers Squibb Company, Princeton, NJ, USA. helen.he1@bms.com
authors.forename: Yaohua
authors.initials: Y
authors.lastname: He
authors.forename: Michael
authors.initials: M
authors.lastname: Escobar
mesh_terms: D000818:Animals; D023281:Genomics / Q000706:statistics & numerical data*; D051379:Mice; D012372:ROC Curve