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dc.date.accessioned2018-11-06T12:35:41Z
dc.date.available2019-08-01T22:46:41Z
dc.date.created2017-12-20T17:38:07Z
dc.date.issued2017
dc.identifier.citationWood, Mollie Chrysanthopoulou, Stavroula Nordeng, Hedvig Marie Egeland Lapane, Kate L. . The impact of nondifferential exposure misclassification on the performance of propensity scores for continuous and binary outcomes: a simulation study. Medical Care. 2017
dc.identifier.urihttp://hdl.handle.net/10852/65410
dc.description.abstractPurpose: To investigate the ability of the propensity score (PS) to reduce confounding bias in the presence of nondifferential misclassification of treatment, using simulations. Methods: Using an example from the pregnancy medication safety literature, we carried out simulations to quantify the effect of nondifferential misclassification of treatment under varying scenarios of sensitivity and specificity, exposure prevalence (10%, 50%), outcome type (continuous and binary), true outcome (null and increased risk), confounding direction, and different PS applications (matching, stratification, weighting, regression), and obtained measures of bias and 95% confidence interval coverage. Results: All methods were subject to substantial bias toward the null due to nondifferential exposure misclassification (range: 0%–47% for 50% exposure prevalence and 0%–80% for 10% exposure prevalence), particularly if specificity was low (< 97%). PS stratification produced the least biased effect estimates. We observed that the impact of sensitivity and specificity on the bias and coverage for each adjustment method is strongly related to prevalence of exposure: as exposure prevalence decreases and/or outcomes are continuous rather than categorical, the effect of misclassification is magnified, producing larger biases and loss of coverage of 95% confidence intervals. PS matching resulted in unpredictably biased effect estimates. Conclusions: The results of this study underline the importance of assessing exposure misclassification in observational studies in the context of PS methods. Although PS methods reduce confounding bias, bias owing to nondifferential misclassification is of potentially greater concern.en_US
dc.languageEN
dc.titleThe impact of nondifferential exposure misclassification on the performance of propensity scores for continuous and binary outcomes: a simulation studyen_US
dc.title.alternativeENEngelskEnglishThe impact of nondifferential exposure misclassification on the performance of propensity scores for continuous and binary outcomes: a simulation study
dc.typeJournal articleen_US
dc.creator.authorWood, Mollie
dc.creator.authorChrysanthopoulou, Stavroula
dc.creator.authorNordeng, Hedvig Marie Egeland
dc.creator.authorLapane, Kate L.
cristin.unitcode185,15,23,10
cristin.unitnameFarmasi
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode2
dc.identifier.cristin1530646
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Medical Care&rft.volume=&rft.spage=&rft.date=2017
dc.identifier.jtitleMedical Care
dc.identifier.pagecount8
dc.identifier.doihttp://dx.doi.org/10.1097/MLR.0000000000000800
dc.identifier.urnURN:NBN:no-68185
dc.type.documentTidsskriftartikkelen_US
dc.type.peerreviewedPeer reviewed
dc.source.issn0025-7079
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/65410/1/Propensity%2Bmisclassification%2BPOSTREVIEW%2BVERSION%2BFOR%2BSELF%2BARCHIVE.pdf
dc.type.versionAcceptedVersion
dc.relation.projectEU/639377


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