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dc.date.accessioned2020-04-20T09:37:12Z
dc.date.created2020-01-21T16:20:06Z
dc.date.issued2019
dc.identifier.citationLupattelli, Angela Wood, Mollie Nordeng, Hedvig Marie Egeland . Analyzing Missing Data in Perinatal Pharmacoepidemiology Research: Methodological Considerations to Limit the Risk of Bias. Clinical Therapeutics. 2019, 41(12), 2477-2487
dc.identifier.urihttp://hdl.handle.net/10852/74638
dc.description.abstractPharmacoepidemiological studies on the safety of medication during pregnancy are all susceptible to missing data (ie, data that should have been recorded but for some reason were not). Missing data are ubiquitous, irrespective of the data source used. Bias can arise when incomplete data on confounders, outcome measures, pregnancy duration, or even cohort selection criteria are used to estimate prenatal exposure effects that would be obtained from the fully observed data, if these were available for each mother–child dyad. This commentary describes general missing data mechanisms and methods, and illustrates how missing data were handled in recent medication in pregnancy research, according to the utilized data source. We further present one applied example on missing data analysis within MoBa (the Norwegian Mother, Father and Child Cohort Study), and finally illustrate how the causal diagram framework can be helpful in assessing risk of bias due to missing data in perinatal pharmacoepidemiology research. We recommend that applied researchers limit missing data during data collection, carefully diagnose missingness, apply strategies for missing data mitigation under different assumptions, and finally include evaluations of robustness results under these assumptions. Following this set of recommendations can aid future perinatal pharmacoepidemiology research in avoiding the problems that result from failure to consider this important source of bias.en_US
dc.languageEN
dc.publisherExcerpta Medica
dc.titleAnalyzing Missing Data in Perinatal Pharmacoepidemiology Research: Methodological Considerations to Limit the Risk of Biasen_US
dc.typeJournal articleen_US
dc.creator.authorLupattelli, Angela
dc.creator.authorWood, Mollie
dc.creator.authorNordeng, Hedvig Marie Egeland
dc.date.embargoenddate2020-11-29
cristin.unitcode185,15,23,10
cristin.unitnameGalenisk farmasi og samfunnsfarmasi
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1
dc.identifier.cristin1779430
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Clinical Therapeutics&rft.volume=41&rft.spage=2477&rft.date=2019
dc.identifier.jtitleClinical Therapeutics
dc.identifier.volume41
dc.identifier.issue12
dc.identifier.startpage2477
dc.identifier.endpage2487
dc.identifier.doihttp://dx.doi.org/10.1016/j.clinthera.2019.11.003
dc.identifier.urnURN:NBN:no-77740
dc.type.documentTidsskriftartikkelen_US
dc.type.peerreviewedPeer reviewed
dc.source.issn0149-2918
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/74638/4/CLINTHER-D-19-00196_R1%281%29.pdf
dc.type.versionAcceptedVersion


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