Principal investigator: Aiyi Liu, Ph.D.
Sensitivity, specificity, and ROC curves along with the area under the curve are important measures for evaluation of diagnostic test or biomarkers (ROC Curve for Biomarkers of Oxidative Stress Assessment) The research focuses on:
- Parametric and nonparametric methods for combination of tests to improve diagnostic accuracy;
- Extension and generalization of the usual concepts of sensitivity, specificity, and ROC curves to studies with special designs, such as naturally matched case-control studies, and studies with pooled assessments or correlated test results; and
- Sequential and adaptive methods that are specific for evaluation of diagnostic tests and biomarkers.
DESPR Collaborators ·
Enrique F. Schisterman, Ph.D.·
Mi-Xia Wu, Ph.D. Selected Publications
Liu A, Schisterman EF, Mazumdar M, & Hu J. (2005). Power and sample size calculation of comparative diagnostic accuracy studies with multiple correlated test results.
Biometrical Journal, 47:140-150.
Liu A, Schisterman EF, & Wu C. (2005). Nonparametric estimation and hypothesis testing on the partial area under receiver operating characteristic curves. Communications in Statistics-
Theory and Methods, 34:1-12.
Liu A, Schisterman EF, & Teoh E. (2004). Sample size and power calculation in comparing diagnostic accuracy of biomarkers with pooled assessments.
Journal of Applied Statistics, 31:49-59.
Liu A & Schisterman EF. (2003). Comparison of diagnostic accuracy of biomarkers with pooled assessments.
Biometrical Journal, 45:631-644.
Mazumdar M & Liu A. (2003). Group sequential design for comparative diagnostic accuracy studies.
Statistics in Medicine, 22:727-739. [
Abstract]
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