Group Sequential Methods for ROC Curves

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dc.contributor.advisorTang, Liansheng L.
dc.contributor.authorYe, Xuan
dc.creatorYe, Xuan
dc.date.accessioned2016-09-28T10:23:02Z
dc.date.available2016-09-28T10:23:02Z
dc.date.issued2015
dc.description.abstractComparative diagnostic studies in which each patient has two tests conducted or has several diseased and nondiseased observations for each test will generate correlated or clustered ROC curves. The traditional ROC comparison methods applied on the correlated or clustered data can result in incorrect statistical inference. Furthermore, to design and apply group sequential method in these comparative trials, we need to derive the theoretical variance-covariance structure and the joint distribution of sequential statistics. We first derive the theoretical covariance structure of sequential correlated and clustered ROCs' difference and further verify the findings through simulation studies. Then based on the independent increments covariance structure that we have proved, we conduct group sequential studies for comparing ROC curves on both simulated and real data.
dc.format.extent165 pages
dc.identifier.urihttps://hdl.handle.net/1920/10446
dc.language.isoen
dc.rightsCopyright 2015 Xuan Ye
dc.subjectStatistics
dc.subjectClustered
dc.subjectCorrelated
dc.subjectGroup Sequential Method
dc.subjectNPV
dc.subjectPPV
dc.subjectROC
dc.titleGroup Sequential Methods for ROC Curves
dc.typeDissertation
thesis.degree.disciplineStatistical Science
thesis.degree.grantorGeorge Mason University
thesis.degree.levelDoctoral

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