Afficher la notice abrégée

dc.rights.licenseopenen_US
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorSAULNIER, Tiphaine
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorPHILIPPS, Viviane
hal.structure.identifierInstitut des Maladies Neurodégénératives [Bordeaux] [IMN]
dc.contributor.authorMEISSNER, Wassilios
IDREF: 113664761
dc.contributor.authorRASCOL, Olivier
dc.contributor.authorPAVY-LE TRAON, Anne
hal.structure.identifierInstitut des Maladies Neurodégénératives [Bordeaux] [IMN]
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorSAMIER FOUBERT, Alexandra
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorPROUST-LIMA, Cecile
dc.date.accessioned2022-04-25T13:51:28Z
dc.date.available2022-04-25T13:51:28Z
dc.date.issued2022-03-10
dc.identifier.issn1046-2023en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/139927
dc.description.abstractEnIn health cohort studies, repeated measures of markers are often used to describe the natural history of a disease. Joint models allow to study their evolution by taking into account the possible informative dropout usually due to clinical events. However, joint modeling developments mostly focused on continuous Gaussian markers while, in an increasing number of studies, the actual quantity of interest is non-directly measurable; it constitutes a latent variable evaluated by a set of observed indicators from questionnaires or measurement scales. Classical examples include anxiety, fatigue, cognition. In this work, we explain how joint models can be extended to the framework of a latent quantity measured over time by indicators of different nature (e.g. continuous, binary, ordinal). The longitudinal submodel describes the evolution over time of the quantity of interest defined as a latent process in a structural mixed model, and links the latent process to each observation of the indicators through appropriate measurement models. Simultaneously, the risk of multi-cause event is modelled via a proportional cause-specific hazard model that includes a function of the mixed model elements as linear predictor to take into account the association between the latent process and the risk of event. Estimation, carried out in the maximum likelihood framework and implemented in the R-package JLPM, has been validated by simulations. The methodology is illustrated in the French cohort on Multiple-System Atrophy (MSA), a rare and fatal neurodegenerative disease, with the study of dysphagia progression over time stopped by the occurrence of death.
dc.description.sponsorshipModèles Dynamiques pour les Etudes Epidémiologiques Longitudinales sur les Maladies Chroniques - ANR-18-CE36-0004en_US
dc.language.isoENen_US
dc.subject.enJoint model
dc.subject.enTime-to-event data
dc.subject.enLongitudinal data
dc.subject.enLatent process
dc.subject.enOrdinal data
dc.title.enJoint models for the longitudinal analysis of measurement scales in the presence of informative dropout
dc.typeArticle de revueen_US
dc.identifier.doi10.1016/j.ymeth.2022.03.003en_US
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
dc.identifier.pubmed35283328en_US
bordeaux.journalMethodsen_US
bordeaux.hal.laboratoriesBordeaux Population Health Research Center (BPH) - UMR 1219en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionINSERMen_US
bordeaux.teamACTIVE_BPHen_US
bordeaux.teamBIOSTAT_BPHen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressouien_US
bordeaux.identifier.funderIDAgence Nationale de la Rechercheen_US
hal.identifierhal-03651289
hal.version1
hal.date.transferred2022-04-25T13:51:32Z
hal.exporttrue
dc.rights.ccPas de Licence CCen_US
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Methods&rft.date=2022-03-10&rft.eissn=1046-2023&rft.issn=1046-2023&rft.au=SAULNIER,%20Tiphaine&PHILIPPS,%20Viviane&MEISSNER,%20Wassilios&RASCOL,%20Olivier&PAVY-LE%20TRAON,%20Anne&rft.genre=article


Fichier(s) constituant ce document

Thumbnail

Ce document figure dans la(les) collection(s) suivante(s)

Afficher la notice abrégée