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dc.rights.licenseopenen_US
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorROUANET, Anais
IDREF: 198306717
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorHELMER, Catherine
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorDARTIGUES, Jean-Francois
ORCID: 0000-0001-9482-5529
IDREF: 058586105
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorJACQMIN-GADDA, Helene
dc.date.accessioned2020-07-10T11:47:28Z
dc.date.available2020-07-10T11:47:28Z
dc.date.issued2019-02
dc.identifier.issn1477-0334 (Electronic) 0962-2802 (Linking)en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/10406
dc.description.abstractEnMixed models estimated by maximum likelihood and marginal models estimated by generalized estimating equations are the standard methods for the analysis of longitudinal data. However, their use is highly debated when attrition may be due to death. While some authors consider that mixed model estimates are interpretable only in an immortal cohort, we show that their subject-specific interpretation still holds in the population currently alive, but their population-averaged interpretation is valid only in the immortal cohort. We propose an approximation of the population-averaged mean among the population alive that highlights the difference with the population-averaged mean in the immortal cohort. The interpretation of ML estimates of mixed models and joint models for the marker and the time-to-death as well as unweighted and weighted GEE of marginal models is then illustrated in a simulation study and in an application regarding cognitive decline in the elderly.
dc.language.isoENen_US
dc.subject.enBiostatistics
dc.subject.enLEHA
dc.subject.enSEPIA
dc.subject.enFR
dc.title.enInterpretation of mixed models and marginal models with cohort attrition due to death and drop-out
dc.title.alternativeStat Methods Med Resen_US
dc.typeArticle de revueen_US
dc.identifier.doi10.1177/0962280217723675en_US
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
dc.identifier.pubmed28784010en_US
bordeaux.journalStatistical Methods in Medical Researchen_US
bordeaux.page343-356en_US
bordeaux.volume28en_US
bordeaux.hal.laboratoriesBordeaux Population Health Research Center (BPH) - U1219en_US
bordeaux.issue2en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.teamLEHA_BPH
bordeaux.teamBIOSTAT_BPH
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
hal.identifierhal-03163178
hal.version1
hal.date.transferred2021-03-09T09:22:41Z
hal.exporttrue
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Statistical%20Methods%20in%20Medical%20Research&rft.date=2019-02&rft.volume=28&rft.issue=2&rft.spage=343-356&rft.epage=343-356&rft.eissn=1477-0334%20(Electronic)%200962-2802%20(Linking)&rft.issn=1477-0334%20(Electronic)%200962-2802%20(Linking)&rft.au=ROUANET,%20Anais&HELMER,%20Catherine&DARTIGUES,%20Jean-Francois&JACQMIN-GADDA,%20Helene&rft.genre=article


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