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Title: Bayesian Correction for Exposure Misclassification and Evolution of Evidence in Two Studies of the Association Between Maternal Occupational Exposure to Asthmagens and Risk of Autism Spectrum Disorder.

Authors: Singer, Alison B; Daniele Fallin, M; Burstyn, Igor

Published In Curr Environ Health Rep, (2018 09)

Abstract: Inference in epidemiologic studies is plagued by exposure misclassification. Several methods exist to correct for misclassification error. One approach is to use point estimates for the sensitivity (Sn) and specificity (Sp) of the tool used for exposure assessment. Unfortunately, we typically do not know the Sn and Sp with certainty. Bayesian methods for exposure misclassification correction allow us to model this uncertainty via distributions for Sn and Sp. These methods have been applied in epidemiologic literature, but are not considered a mainstream approach, especially in occupational epidemiology.Here, we illustrate an occupational epidemiology application of a Bayesian approach to correct for the differential misclassification error generated by estimating occupational exposures from job codes using a job exposure matrix (JEM). We argue that analyses accounting for exposure misclassification should become more commonplace in the literature.

PubMed ID: 30030714 Exiting the NIEHS site

MeSH Terms: No MeSH terms associated with this publication

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