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A method for sensitivity analysis to assess the effects of measurement error in multiple exposure variables using external validation data

BMC medical research methodology, 2016-10, Vol.16 (1), p.139-139, Article 139 [Peer Reviewed Journal]

COPYRIGHT 2016 BioMed Central Ltd. ;Copyright BioMed Central 2016 ;info:eu-repo/semantics/openAccess ;The Author(s). 2016 ;Wageningen University & Research ;ISSN: 1471-2288 ;EISSN: 1471-2288 ;DOI: 10.1186/s12874-016-0240-1 ;PMID: 27737637

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Title:
A method for sensitivity analysis to assess the effects of measurement error in multiple exposure variables using external validation data
Author: Agogo, George O ; van der Voet, Hilko ; van 't Veer, Pieter ; Ferrari, Pietro ; Muller, David C ; Sánchez-Cantalejo, Emilio ; Bamia, Christina ; Braaten, Tonje ; Knüppel, Sven ; Johansson, Ingegerd ; van Eeuwijk, Fred A ; Boshuizen, Hendriek C
Subjects: Attenuation-contamination matrix ; Bayesian MCMC ; Bias ; Cancer ; Cigarettes ; Community medicine, Social medicine: 801 ; Consent ; Consortia ; Diet ; Diet - adverse effects ; Disease ; EPIC study ; Epidemiology ; Fruits ; Health aspects ; Health risk assessment ; Health sciences: 800 ; Helsefag: 800 ; Humans ; Measurement ; Measurement error ; Medical disciplines: 700 ; Medical errors ; Medisinske Fag: 700 ; Methods ; Mortality ; Multicenter Studies as Topic ; Multivariate Analysis ; Neoplasms - epidemiology ; Neoplasms - etiology ; Nutrition research ; Proportional Hazards Models ; Prospective Studies ; Researchers ; Risk Assessment ; Samfunnsmedisin, sosialmedisin: 801 ; Self Report ; Sensitivity and Specificity ; Smoking ; Smoking - adverse effects ; Validation studies ; Validation Studies as Topic ; Validation study ; Validity ; Variables ; VDP
Is Part Of: BMC medical research methodology, 2016-10, Vol.16 (1), p.139-139, Article 139
Description: 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. 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 literature-reported 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. 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. 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.
Publisher: England: BioMed Central Ltd
Language: English
Identifier: ISSN: 1471-2288
EISSN: 1471-2288
DOI: 10.1186/s12874-016-0240-1
PMID: 27737637
Source: TestCollectionTL3OpenAccess
GFMER Free Medical Journals
MEDLINE
NORA Norwegian Open Research Archives
PubMed Central
SWEPUB Freely available online
Springer Nature OA/Free Journals
ROAD: Directory of Open Access Scholarly Resources
ProQuest Central

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A method for sensitivity analysis to assess the effects of measurement error in multiple exposure variables using external validation data

COPYRIGHT 2016 BioMed Central Ltd. ;Copyright BioMed Central 2016 ;info:eu-repo/semantics/openAccess ;The Author(s). 2016 ;Wageningen University & Research ;ISSN: 1471-2288 ;EISSN: 1471-2288 ;DOI: 10.1186/s12874-016-0240-1 ;PMID: 27737637

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