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Methods to Explore Uncertainty and Bias Introduced by Job Exposure Matrices

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  • Sander Greenland
  • Heidi J. Fischer
  • Leeka Kheifets
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.

Suggested Citation

  • Sander Greenland & Heidi J. Fischer & Leeka Kheifets, 2016. "Methods to Explore Uncertainty and Bias Introduced by Job Exposure Matrices," Risk Analysis, John Wiley & Sons, vol. 36(1), pages 74-82, January.
    • Handle: RePEc:wly:riskan:v:36:y:2016:i:1:p:74-82
    DOI: 10.1111/risa.12438
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    References listed on IDEAS

    as
    1. Nicola Orsini & Rino Bellocco & Matteo Bottai & Alicja Wolk & Sander Greenland, 2008. "A tool for deterministic and probabilistic sensitivity analysis of epidemiologic studies," Stata Journal, StataCorp LP, vol. 8(1), pages 29-48, February.
    2. Raydonal Ospina & Silvia Ferrari, 2010. "Inflated beta distributions," Statistical Papers, Springer, vol. 51(1), pages 111-126, January.
    3. Sander Greenland, 2000. "When Should Epidemiologic Regressions Use Random Coefficients?," Biometrics, The International Biometric Society, vol. 56(3), pages 915-921, September.
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