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dc.rights.licenseopenen_US
dc.contributor.authorWU, Yingyan
dc.contributor.authorHAYES-LARSON, Eleanor
dc.contributor.authorZHOU, Yixuan
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorBOUTELOUP, Vincent
dc.contributor.authorZIMMERMAN, Scott C
dc.contributor.authorPEDERSON, Anna M
hal.structure.identifierInstitut des Maladies Neurodégénératives [Bordeaux] [IMN]
dc.contributor.authorPLANCHE, Vincent
dc.contributor.authorSEAMANS, Marissa J
dc.contributor.authorWESTREICH, Daniel
dc.contributor.authorGLYMOUR, M Maria
dc.contributor.authorGIBBONS, Laura E
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorDUFOUIL, Carole
dc.contributor.authorMAYEDA, Elizabeth Rose
dc.date.accessioned2025-02-21T10:37:01Z
dc.date.available2025-02-21T10:37:01Z
dc.date.issued2025-01-10
dc.identifier.issn1047-2797en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/205097
dc.description.abstractEnPURPOSE: Harmonizing variables for constructs measured differently across studies is essential for comparing, combining, and generalizing results. We developed and fielded a brief survey to harmonize Likert and continuous versions of measures for two constructs, self-rated health and self-rated memory, for use in studies of French older adults. METHODS: We recruited 300 participants from a French memory clinic in 2023 to answer both the Likert and continuous versions of self-rated health and self-rated memory questions. For each construct, we predicted responses to the Likert version with multinomial and ordinal logistic models, varying specifications of continuous version responses (linear or spline) and covariate sets (question order, age, sex/gender, and interactions between the continuous version and covariates). We also implemented a percentiles-based crosswalk sensitivity analysis. We compared Cohen's weighted kappa values to identify the best statistical harmonization approach. RESULTS: In the final models [multinomial models with continuous version spline, question order (self-rated memory model only), age, sex/gender, and interactions between the continuous version and covariates], weighted kappa values were 0.61 for self-rated health and 0.60 for self-rated memory, reflecting moderate agreement. CONCLUSIONS: Primary data collection feasibly facilitates statistical harmonization of variables for constructs measured differently across studies.
dc.language.isoENen_US
dc.subject.enMeasurement
dc.subject.enPrimary data collection
dc.subject.enStatistical harmonization
dc.title.enStatistical harmonization of versions of measures across studies using external data: Self-rated health and self-rated memory
dc.title.alternativeAnn Epidemiolen_US
dc.typeArticle de revueen_US
dc.identifier.doi10.1016/j.annepidem.2025.01.002en_US
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
dc.identifier.pubmed39800088en_US
bordeaux.journalAnnals of Epidemiologyen_US
bordeaux.page86-90en_US
bordeaux.volume102en_US
bordeaux.hal.laboratoriesBordeaux Population Health Research Center (BPH) - UMR 1219en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionINSERMen_US
bordeaux.institutionCNRS
bordeaux.teamPHARES_BPHen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
hal.identifierhal-04960437
hal.version1
hal.date.transferred2025-02-21T10:37:05Z
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exporttrue
dc.rights.ccPas de Licence CCen_US
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