Nonparametric estimation and inference for polytomous discrimination index.
Polytomous discrimination index is a novel and important diagnostic accuracy measure for multi-category classification. After reconstructing its probabilistic definition, we propose a nonparametric approach to the estimation of polytomous discrimination index based on an empirical sample of biomarker values. In this paper, we provide the finite-sample and asymptotic properties of the proposed estimators and such analytic results may facilitate the statistical inference. Simulation studies are performed to examine the performance of the nonparametric estimators. Two real data examples are analysed to illustrate our methodology.
1 National University of Singapore, Singapore, Singapore.|2 Duke-NUS Graduate Medical School, Singapore, Singapore.|3 Singapore Eye Research Institute, Singapore, Singapore.
Jialiang
J
Li
1 National University of Singapore, Singapore, Singapore.|4 University of Science and Technology of China, Hefei Shi, China.
Qunqiang
Q
Feng
5 University of North Carolina, Chapel Hill, USA.
Jason P
JP
Fine
6 Duke University, Durham, USA.
Michael J
MJ
Pencina
7 University of Leuven, Leuven, Belgium.
Ben
B
Van Calster
D015415:Biomarkers / Q000032:analysis; D003627:Data Interpretation, Statistical; D016208:Databases, Factual / Q000706:statistics & numerical data; D004534:Egypt; D006801:Humans; D008113:Liver Neoplasms / Q000175:diagnosis; D016015:Logistic Models; D013058:Mass Spectrometry; D012372:ROC Curve; D018709:Statistics, Nonparametric
D015415:Biomarkers
Polytomous discrimination index; diagnostic medicine; multi-category classification; multi-sample U-statistics; nonparametric estimation