Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/25784

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dc.contributor.authorMachado, Luís Meira-
dc.contributor.authorCadarso-Suárez, Carmen-
dc.contributor.authorGude, Francisco-
dc.contributor.authorAraújo, Artur Agostinho-
dc.date.accessioned2013-10-18T11:03:46Z-
dc.date.available2013-10-18T11:03:46Z-
dc.date.issued2013-10-
dc.date.submitted2013-07-
dc.identifier.issn1748-670Xpor
dc.identifier.urihttp://hdl.handle.net/1822/25784-
dc.descriptionProva tipográficapor
dc.description.abstractThe Cox proportional hazards regression model has become the traditional choice for modeling survival data in medical studies. Usually, this model is assumed to be (semi)parametric, and the effects of continuous predictors on log-hazards are modeled linearly. In practice, however, the effect of a given continuous predictor can be unknown. To introduce flexibility into the Cox model, several smoothing methods may be applied, and approaches based on splines are the most frequently considered in this context. To better understand the effects that each continuous covariate has on the outcome, results can be expressed in terms of splines-based hazard ratio (HR) curves, taking a specific covariate value as reference. Despite the potential advantages of using spline smoothing methods in survival analysis, there is currently no analytical method in the R software to choose the optimal degrees of freedom in multivariable Cox models (with two or more nonlinear covariate e ects). This paper describes an R package, called smoothHR, that allows the computation of pointwise estimates of the HRs -and their corresponding confidence limits- of continuous predictors introduced nonlinearly. In addition the package provides a function for choosing automatically the degrees of freedom in multivariable Cox models. The package is available from the R homepage http://cran.r-project.org. We illustrate the use of the key functions of the smoothHR package using data from a study on breast cancer and data on acute coronary syndrome, from Galicia, Spain.por
dc.description.sponsorshipLuis Meira-Machado acknowledges financial support by FEDER Funds through Programa Operacional Factores de Competitividade COMPETE and by Portuguese Funds through FCT - Funda ção para a Ciência e a Tecnologia, within Projects Est-C/MAT/UI0013/2011 and PTDC/MAT/104879/2008. Luí s Meira-Machado and Carmen Cadarso- Su árez acknowledge the support received by the Spanish Ministry of Industry and Innovation, Grant MTM2011-28285-C02-01.por
dc.language.isoengpor
dc.publisherHindawi Publishing Corporationpor
dc.rightsrestrictedAccesspor
dc.subjectHazard ratiopor
dc.subjectSurvival analysispor
dc.subjectCox modelpor
dc.subjectGeneralized additive modelpor
dc.subjectSmoothingpor
dc.titlesmoothHR: an R package for pointwise nonparametric estimation of hazard ratio curves of continuous predictorspor
dc.typearticlepor
dc.peerreviewedyespor
dc.relation.publisherversionhttp://www.hindawi.com/journals/cmmm/aip/745742/por
sdum.publicationstatusin publicationpor
oaire.citationStartPage1por
oaire.citationEndPage24por
oaire.citationTitleComputational and Mathematical Methods in Medicinepor
oaire.citationVolume2013por
dc.identifier.doi10.1155/2013/745742por
dc.identifier.pmid24454541por
dc.subject.wosScience & Technologypor
sdum.journalComputational and Mathematical Methods in Medicinepor
Appears in Collections:CMAT - Artigos em revistas com arbitragem / Papers in peer review journals

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