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Inverse probability weighting to control confounding in an illness-death model for interval-censored data

dc.rights.licenseopenen_US
dc.contributor.authorGILLAIZEAU, F.
dc.contributor.authorSENAGE, T.
dc.contributor.authorLE BORGNE, F.
dc.contributor.authorLE TOURNEAU, T.
dc.contributor.authorROUSSEL, J. C.
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorLEFFONDRE, Karen
IDREF: 183599128
dc.contributor.authorPORCHER, R.
dc.contributor.authorGIRAUDEAU, B.
dc.contributor.authorDANTAN, E.
dc.contributor.authorFOUCHER, Y.
dc.date.accessioned2020-11-10T13:53:34Z
dc.date.available2020-11-10T13:53:34Z
dc.date.issued2018-04-15
dc.identifier.issn1097-0258 (Electronic) 0277-6715 (Linking)en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/12208
dc.description.abstractEnMultistate models with interval-censored data, such as the illness-death model, are still not used to any considerable extent in medical research regardless of the significant literature demonstrating their advantages compared to usual survival models. Possible explanations are their uncommon availability in classical statistical software or, when they are available, by the limitations related to multivariable modelling to take confounding into consideration. In this paper, we propose a strategy based on propensity scores that allows population causal effects to be estimated: the inverse probability weighting in the illness semi-Markov model with interval-censored data. Using simulated data, we validated the performances of the proposed approach. We also illustrated the usefulness of the method by an application aiming to evaluate the relationship between the inadequate size of an aortic bioprosthesis and its degeneration or/and patient death. We have updated the R package multistate to facilitate the future use of this method.
dc.language.isoENen_US
dc.subject.enBiostatistics
dc.title.enInverse probability weighting to control confounding in an illness-death model for interval-censored data
dc.title.alternativeStat Meden_US
dc.typeArticle de revueen_US
dc.identifier.doi10.1002/sim.7550en_US
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
dc.identifier.pubmed29205409en_US
bordeaux.journalStatistics in medicineen_US
bordeaux.page1245-1258en_US
bordeaux.volume37en_US
bordeaux.hal.laboratoriesBordeaux Population Health Research Center (BPH) - U1219en_US
bordeaux.issue8en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.teamBIOSTAT_BPHen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
hal.exportfalse
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