title: A method for sensitivity analysis to assess the effects of measurement error in multiple exposure variables using external validation data.
abstract: 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.
authors.affiliation: Biometris, Wageningen University and Research Centre, Wageningen, The Netherlands. george.agogo@yale.edu.|Department of Internal Medicine, Yale University, New Haven, USA. george.agogo@yale.edu.
authors.forename: George O
authors.initials: GO
authors.lastname: Agogo
authors.affiliation: Biometris, Wageningen University and Research Centre, Wageningen, The Netherlands.
authors.forename: Hilko
authors.initials: H
authors.lastname: van der Voet
authors.affiliation: Department of Human Nutrition, Wageningen University and Research Centre, Wageningen, The Netherlands.
authors.forename: Pieter
authors.initials: P
authors.lastname: van 't Veer
authors.affiliation: Nutritional Epidemiology Group, International Agency for Research on Cancer, Lyon, France.
authors.forename: Pietro
authors.initials: P
authors.lastname: Ferrari
authors.affiliation: Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France.
authors.forename: David C
authors.initials: DC
authors.lastname: Muller
authors.affiliation: Andalusian School of Public Health, Granada, Spain.
authors.forename: Emilio
authors.initials: E
authors.lastname: Sánchez-Cantalejo
authors.affiliation: Department of Hygiene, Epidemiology and Medical Statistics, University of Athens Medical School, Athens, Greece.
authors.forename: Christina
authors.initials: C
authors.lastname: Bamia
authors.affiliation: Department of Community Medicine, University of Tromsø, N-9037, Tromsø, Norway.
authors.forename: Tonje
authors.initials: T
authors.lastname: Braaten
authors.affiliation: Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal, Germany.
authors.forename: Sven
authors.initials: S
authors.lastname: Knüppel
authors.affiliation: Department of Odontology, Umeå university, Umeå, Sweden.
authors.forename: Ingegerd
authors.initials: I
authors.lastname: Johansson
authors.affiliation: Biometris, Wageningen University and Research Centre, Wageningen, The Netherlands.
authors.forename: Fred A
authors.initials: FA
authors.lastname: van Eeuwijk
authors.affiliation: Department of Statistics, mathematical modelling and data logistics, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.
authors.forename: Hendriek C
authors.initials: HC
authors.lastname: Boshuizen
mesh_terms: D015982:Bias; D004032:Diet / Q000009:adverse effects; D006801:Humans; D015337:Multicenter Studies as Topic; D015999:Multivariate Analysis; D009369:Neoplasms / Q000453:epidemiology* / Q000209:etiology; D016016:Proportional Hazards Models; D011446:Prospective Studies; D018570:Risk Assessment; D057566:Self Report; D012680:Sensitivity and Specificity; D012907:Smoking / Q000009:adverse effects; D054928:Validation Studies as Topic
keywords: Attenuation-contamination matrix; Bayesian MCMC; EPIC study; Measurement error; Validation study