Alison B Singer1,2,3, M Daniele Fallin1,2,4, Igor Burstyn5,6,7. 1. Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA. 2. Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA. 3. Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 4. Department of Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA. 5. Department of Environmental and Occupational Health, Drexel University Dornsife School of Public Health, Philadelphia, PA, USA. igor.burstyn@drexel.edu. 6. Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA, USA. igor.burstyn@drexel.edu. 7. A.J. Drexel Autism Institute, Drexel University Dornsife School of Public Health, Philadelphia, PA, USA. igor.burstyn@drexel.edu.
Abstract
PURPOSE OF REVIEW: 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. RECENT FINDINGS: 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.
PURPOSE OF REVIEW: 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. RECENT FINDINGS: 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.
Authors: Diana E Schendel; Carolyn Diguiseppi; Lisa A Croen; M Daniele Fallin; Philip L Reed; Laura A Schieve; Lisa D Wiggins; Julie Daniels; Judith Grether; Susan E Levy; Lisa Miller; Craig Newschaffer; Jennifer Pinto-Martin; Cordelia Robinson; Gayle C Windham; Aimee Alexander; Arthur S Aylsworth; Pilar Bernal; Joseph D Bonner; Lisa Blaskey; Chyrise Bradley; Jack Collins; Casara J Ferretti; Homayoon Farzadegan; Ellen Giarelli; Marques Harvey; Susan Hepburn; Matthew Herr; Kristina Kaparich; Rebecca Landa; Li-Ching Lee; Brooke Levenseller; Stacey Meyerer; Mohammad H Rahbar; Andria Ratchford; Ann Reynolds; Steven Rosenberg; Julie Rusyniak; Stuart K Shapira; Karen Smith; Margaret Souders; Patrick Aaron Thompson; Lisa Young; Marshalyn Yeargin-Allsopp Journal: J Autism Dev Disord Date: 2012-10
Authors: Alison B Singer; Igor Burstyn; Malene Thygesen; Preben Bo Mortensen; M Daniele Fallin; Diana E Schendel Journal: Environ Health Date: 2017-03-31 Impact factor: 5.984
Authors: Alison B Singer; Gayle C Windham; Lisa A Croen; Julie L Daniels; Brian K Lee; Yinge Qian; Diana E Schendel; M Daniele Fallin; Igor Burstyn Journal: J Autism Dev Disord Date: 2016-11