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dc.rights.licenseopenen_US
dc.contributor.authorLUSA, Lara
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorPROUST-LIMA, Cecile
dc.contributor.authorSCHMIDT, Carsten O
dc.contributor.authorLEE, Katherine J
dc.contributor.authorLE CESSIE, Saskia
dc.contributor.authorBAILLIE, Mark
dc.contributor.authorLAWRENCE, Frank
dc.contributor.authorHUEBNER, Marianne
dc.contributor.authorINITIATIVE, T. G. Of The STRATOS
dc.date.accessioned2024-10-15T07:52:36Z
dc.date.available2024-10-15T07:52:36Z
dc.date.issued2024-05-29
dc.identifier.issn1932-6203en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/202499
dc.description.abstractEnInitial data analysis (IDA) is the part of the data pipeline that takes place between the end of data retrieval and the beginning of data analysis that addresses the research question. Systematic IDA and clear reporting of the IDA findings is an important step towards reproducible research. A general framework of IDA for observational studies includes data cleaning, data screening, and possible updates of pre-planned statistical analyses. Longitudinal studies, where participants are observed repeatedly over time, pose additional challenges, as they have special features that should be taken into account in the IDA steps before addressing the research question. We propose a systematic approach in longitudinal studies to examine data properties prior to conducting planned statistical analyses. In this paper we focus on the data screening element of IDA, assuming that the research aims are accompanied by an analysis plan, meta-data are well documented, and data cleaning has already been performed. IDA data screening comprises five types of explorations, covering the analysis of participation profiles over time, evaluation of missing data, presentation of univariate and multivariate descriptions, and the depiction of longitudinal aspects. Executing the IDA plan will result in an IDA report to inform data analysts about data properties and possible implications for the analysis plan-another element of the IDA framework. Our framework is illustrated focusing on hand grip strength outcome data from a data collection across several waves in a complex survey. We provide reproducible R code on a public repository, presenting a detailed data screening plan for the investigation of the average rate of age-associated decline of grip strength. With our checklist and reproducible R code we provide data analysts a framework to work with longitudinal data in an informed way, enhancing the reproducibility and validity of their work.
dc.language.isoENen_US
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.title.enInitial data analysis for longitudinal studies to build a solid foundation for reproducible analysis
dc.title.alternativePLoS Oneen_US
dc.typeArticle de revueen_US
dc.identifier.doi10.1371/journal.pone.0295726en_US
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
dc.identifier.pubmed38809844en_US
bordeaux.journalPLoS ONEen_US
bordeaux.pagee0295726en_US
bordeaux.volume19en_US
bordeaux.hal.laboratoriesBordeaux Population Health Research Center (BPH) - UMR 1219en_US
bordeaux.issue5en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionINSERMen_US
bordeaux.teamBIOSTAT_BPHen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
hal.identifierhal-04736819
hal.version1
hal.date.transferred2024-10-15T07:52:39Z
hal.popularnonen_US
hal.audienceInternationaleen_US
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=PLoS%20ONE&rft.date=2024-05-29&rft.volume=19&rft.issue=5&rft.spage=e0295726&rft.epage=e0295726&rft.eissn=1932-6203&rft.issn=1932-6203&rft.au=LUSA,%20Lara&PROUST-LIMA,%20Cecile&SCHMIDT,%20Carsten%20O&LEE,%20Katherine%20J&LE%20CESSIE,%20Saskia&rft.genre=article


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