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dc.contributor.authorAgogo, George O.
dc.contributor.authorvan der Voet, Hilko
dc.contributor.authorVan 'T Veer, Pieter
dc.contributor.authorFerrari, Pietro
dc.contributor.authorMuller, David
dc.contributor.authorSánchez-Cantalejo, Emilio
dc.contributor.authorBamia, Christina
dc.contributor.authorBraaten, Tonje
dc.contributor.authorKnüppel, Sven
dc.contributor.authorJohansson, Ingegerd
dc.contributor.authorVan Eeuwijk, Fred A.
dc.contributor.authorBoshuizen, Hendriek C.
dc.date.accessioned2017-02-24T09:58:00Z
dc.date.available2017-02-24T09:58:00Z
dc.date.issued2016-10-13
dc.description.abstractBackground:<br>Measurement error in self-reported dietary intakes is known to bias the association between dietary intake and a health outcome of interest such as risk of a disease. The association can be distorted further by mismeasured confounders, leading to invalid results and conclusions. It is, however, difficult to adjust for the bias in the association when there is no internal validation data.<br> Methods:<br>We proposed a method to adjust for the bias in the diet-disease association (hereafter, association), due to measurement error in dietary intake and a mismeasured confounder, when there is no internal validation data. The method combines prior information on the validity of the self-report instrument with the observed data to adjust for the bias in the association. We compared the proposed method with the method that ignores the confounder effect, and with the method that ignores measurement errors completely. We assessed the sensitivity of the estimates to various magnitudes of measurement error, error correlations and uncertainty in the literaturereported validation data. We applied the methods to fruits and vegetables (FV) intakes, cigarette smoking (confounder) and all-cause mortality data from the European Prospective Investigation into Cancer and Nutrition study.<br> Results:<br> Using the proposed method resulted in about four times increase in the strength of association between FV intake and mortality. For weakly correlated errors, measurement error in the confounder minimally affected the hazard ratio estimate for FV intake. The effect was more pronounced for strong error correlations.<br> Conclusions:<br> The proposed method permits sensitivity analysis on measurement error structures and accounts for uncertainties in the reported validity coefficients. The method is useful in assessing the direction and quantifying the magnitude of bias in the association due to measurement errors in the confounders.<br> Keywords:<br> Attenuation-contamination matrix, Bayesian MCMC, EPIC study, Measurement error, Validation studyen_US
dc.description.sponsorshipThis work was supported financially by a PhD grant for GOA funded by Wageningen University and Research Centre (WUR) and National Institute for Public Health and the Environment (RIVM).en_US
dc.descriptionSource: <a href=http://dx.doi.org/10.1186/s12874-016-0240-1>doi: 10.1186/s12874-016-0240-1</a>en_US
dc.identifier.citationAgogo GO, van der Voet H, Van 'T Veer P, Ferrari P, Muller D, Sánchez-Cantalejo E, Bamia C, Braaten T, Knüppel S, Johansson I, Van Eeuwijk FA, Boshuizen HC. A method for sensitivity analysis to assess the effects of measurement error in multiple exposure variables using external validation data. BMC Medical Research Methodology. 2016;16:139en_US
dc.identifier.cristinIDFRIDAID 1412635
dc.identifier.doi10.1186/s12874-016-0240-1
dc.identifier.issn1471-2288
dc.identifier.urihttps://hdl.handle.net/10037/10358
dc.language.isoengen_US
dc.publisherBioMed Centralen_US
dc.relation.journalBMC Medical Research Methodology
dc.rights.accessRightsopenAccessen_US
dc.subjectVDP::Medisinske Fag: 700::Helsefag: 800::Samfunnsmedisin, sosialmedisin: 801en_US
dc.subjectVDP::Medical disciplines: 700::Health sciences: 800::Community medicine, Social medicine: 801en_US
dc.titleA method for sensitivity analysis to assess the effects of measurement error in multiple exposure variables using external validation dataen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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