title: Methods to Explore Uncertainty and Bias Introduced by Job Exposure Matrices.
abstract: Job exposure matrices (JEMs) are used to measure exposures based on information about particular jobs and tasks. JEMs are especially useful when individual exposure data cannot be obtained. Nonetheless, there may be other workplace exposures associated with the study disease that are not measured in available JEMs. When these exposures are also associated with the exposures measured in the JEM, biases due to uncontrolled confounding will be introduced. Furthermore, individual exposures differ from JEM measurements due to differences in job conditions and worker practices. Uncertainty may also be present at the assessor level since exposure information for each job may be imprecise or incomplete. Assigning individuals a fixed exposure determined by the JEM ignores these uncertainty sources. We examine the uncertainty displayed by bias analyses in a study of occupational electric shocks, occupational magnetic fields, and amyotrophic lateral sclerosis.
authors.affiliation: Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA, USA.|Department of Statistics, College of Letters and Science, University of California, Los Angeles, CA, USA.
authors.forename: Sander
authors.initials: S
authors.lastname: Greenland
authors.affiliation: Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA, USA.
authors.forename: Heidi J
authors.initials: HJ
authors.lastname: Fischer
authors.affiliation: Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA, USA.
authors.forename: Leeka
authors.initials: L
authors.lastname: Kheifets
mesh_terms: D006801:Humans; D015588:Observer Variation; D016273:Occupational Exposure; D035501:Uncertainty
keywords: Bayesian methods; bias analysis; epidemiology; job exposure matrices; occupational risks; sensitivity analysis