Accommodating covariates in receiver operating characteristic analysis

dc.creatorJanes, Holly
dc.creatorLongton, Gary M.
dc.creatorPepe, Margaret S.
dc.date2017-04-01T19:43:16Z
dc.date.accessioned2026-07-09T06:01:23Z
dc.descriptionClassification accuracy is the ability of a marker or diagnostic test to discriminate between two groups of individuals, cases and controls, and is commonly summarized by using the receiver operating characteristic (ROC) curve. In studies of classification accuracy, there are often covariates that should be incorporated into the ROC analysis. We describe three ways of using covariate information. For factors that affect marker observations among controls, we present a method for covariate adjustment. For factors that affect discrimination (i.e., the ROC curve), we describe methods for modeling the ROC curve as a function of covariates. Finally, for factors that contribute to discrimination, we propose combining the marker and covariate information, and we ask how much discriminatory accuracy improves (in incremental value) with the addition of the marker to the covariates. These methods follow naturally when representing the ROC curve as a summary of the distribution of case marker observations, standardized with respect to the control distribution.
dc.identifierOther:st0155
dc.identifierdoi:10.22004/ag.econ.122695
dc.identifierhttps://ageconsearch.umn.edu/record/122695/files/sjart_st0155.pdf
dc.identifierhttp://ageconsearch.umn.edu/record/122695
dc.identifier.urihttp://hdl.handle.net/123456789/571385
dc.languageeng
dc.publisher
dc.sourcehttp://ageconsearch.umn.edu/record/122695
dc.titleAccommodating covariates in receiver operating characteristic analysis
dc.typeText

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