Document Detail

Nonparametric ROC summary statistics for correlated diagnostic marker data.
MedLine Citation:
PMID:  23055248     Owner:  NLM     Status:  Publisher    
We propose efficient nonparametric statistics to compare medical imaging modalities in multi-reader multi-test data and to compare markers in longitudinal ROC data. The proposed methods are based on the weighted area under the ROC curve, which includes the area under the curve and the partial area under the curve as special cases. The methods maximize the local power for detecting the difference between imaging modalities. We develop the asymptotic results of the proposed methods under a complex correlation structure. Our simulation studies show that the proposed statistics result in much better powers than existing statistics. We apply the proposed statistics to an endometriosis diagnosis study. Copyright © 2012 John Wiley & Sons, Ltd.
Liansheng Larry Tang; Aiyi Liu; Zhen Chen; Enrique F Schisterman; Bo Zhang; Zhuang Miao
Related Documents :
19466318 - Keratoconus prediction using a finite element model of the cornea with local biomechani...
18342418 - Sensitivity analysis of a parameterization of the stomatal component of the do3se model...
12445608 - Validation data for periprosthetic bone remodelling theories.
15749208 - Three-dimensional finite element analysis used to compare methods of fixation after sag...
17943708 - Analysis of a nonsusceptible fraction with current status data.
12369638 - Monitoring leaking gases by op-ftir remote sensing.
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-10-11
Journal Detail:
Title:  Statistics in medicine     Volume:  -     ISSN:  1097-0258     ISO Abbreviation:  Stat Med     Publication Date:  2012 Oct 
Date Detail:
Created Date:  2012-10-11     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8215016     Medline TA:  Stat Med     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2012 John Wiley & Sons, Ltd.
Department of Statistics, George Mason University, Fairfax, VA 22030, U.S.A.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

Previous Document:  Current issues in chronic myeloid leukemia: monitoring, resistance, and functional cure.
Next Document:  Sulfur and Nitrogen Dual-Doped Mesoporous Graphene Electrocatalyst for Oxygen Reduction with Synergi...