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dc.contributor.authorRodríguez-Álvarez, M.X.
dc.contributor.authorRoca-Pardiñas, J.
dc.contributor.authorCadarso-Suárez, C.
dc.contributor.authorTahoces, P.G.
dc.date12/12/2018en_US
dc.date.accessioned2017-12-22T10:03:07Z
dc.date.available2017-12-22T10:03:07Z
dc.date.issued2017
dc.identifier.issn0962-2802
dc.identifier.urihttp://hdl.handle.net/20.500.11824/757
dc.description.abstractPrior to using a diagnostic test in a routine clinical setting, the rigorous evaluation of its diagnostic accuracy is essential. The receiver-operating characteristic curve is the measure of accuracy most widely used for continuous diagnostic tests. However, the possible impact of extra information about the patient (or even the environment) on diagnostic accuracy also needs to be assessed. In this paper, we focus on an estimator for the covariate-specific receiver-operating characteristic curve based on direct regression modelling and nonparametric smoothing techniques. This approach defines the class of generalised additive models for the receiver-operating characteristic curve. The main aim of the paper is to offer new inferential procedures for testing the effect of covariates on the conditional receiver-operating characteristic curve within the above-mentioned class. Specifically, two different bootstrap-based tests are suggested to check (a) the possible effect of continuous covariates on the receiver-operating characteristic curve and (b) the presence of factor-by-curve interaction terms. The validity of the proposed bootstrap-based procedures is supported by simulations. To facilitate the application of these new procedures in practice, an R-package, known as npROCRegression, is provided and briefly described. Finally, data derived from a computer-aided diagnostic system for the automatic detection of tumour masses in breast cancer is analyseden_US
dc.formatapplication/pdfen_US
dc.language.isoengen_US
dc.rightsReconocimiento-NoComercial-CompartirIgual 3.0 Españaen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/en_US
dc.subjectReceiver-operating characteristic curveen_US
dc.subjectgeneralised additive modelsen_US
dc.subjectbootstrapen_US
dc.subjectcomputer-aided diagnosisen_US
dc.titleBootstrap-based procedures for inference in nonparametric receiver-operating characteristic curve regression analysisen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.relation.publisherversionhttp://journals.sagepub.com/eprint/zYHPMw6fsCXwyXqy6qES/fullen_US
dc.relation.projectIDES/1PE/SEV-2013-0323en_US
dc.relation.projectIDEUS/BERC/BERC.2014-2017en_US
dc.rights.accessRightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersionen_US
dc.journal.titleStatistical Methods in Medical Researchen_US


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Reconocimiento-NoComercial-CompartirIgual 3.0 España
Except where otherwise noted, this item's license is described as Reconocimiento-NoComercial-CompartirIgual 3.0 España