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In a multicenter study, the overall relationship between diet and cancer risk can be broken down into: (a) within‐center relationships, which reflect the relationships at the individual level in each of the centers, and (b) a between‐center relationship, which captures the association between exposure and disease risk at the aggregate level. In this work, we propose the use of a Bayesian multilevel model that takes into account the within‐ and between‐center levels of evidence, using information at the individual and aggregate level. Correction for measurement error is performed in order to correct for systematic between‐center measurement error in dietary exposure, and for attenuation biases in relative risk estimates within centers. The estimation of the parameters is carried out in a Bayesian framework using Gibbs sampling. The model entails a measurement, an exposure, and a disease component. Within the …