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Bounding Analysis as an Inadequately Specified Methodology

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  • Sander Greenland

Abstract

The bounding analysis methodology described by Ha‐Duong et al. (this issue) is logically incomplete and invites serious misuse and misinterpretation, as their own example and interpretation illustrate. A key issue is the extent to which these problems are inherent in their methodology, and resolvable by a logically complete assessment (such as Monte Carlo or Bayesian risk assessment), as opposed to being general problems in any risk‐assessment methodology. I here attempt to apportion the problems between those inherent in the proposed bounding analysis and those that are more general, such as reliance on questionable expert elicitations. I conclude that the specific methodology of Ha‐Duong et al. suffers from logical gaps in the definition and construction of inputs, and hence should not be used in the form proposed. Furthermore, the labor required to do a sound bounding analysis is great enough so that one may as well skip that analysis and carry out a more logically complete probabilistic analysis, one that will better inform the consumer of the appropriate level uncertainty. If analysts insist on carrying out a bounding analysis in place of more thorough assessments, extensive analyses of sensitivity to inputs and assumptions will be essential to display uncertainties, arguably more essential than it would be in full probabilistic analyses.

Suggested Citation

  • Sander Greenland, 2004. "Bounding Analysis as an Inadequately Specified Methodology," Risk Analysis, John Wiley & Sons, vol. 24(5), pages 1085-1092, October.
  • Handle: RePEc:wly:riskan:v:24:y:2004:i:5:p:1085-1092
    DOI: 10.1111/j.0272-4332.2004.00509.x
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    References listed on IDEAS

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    1. Sander Greenland, 2001. "Sensitivity Analysis, Monte Carlo Risk Analysis, and Bayesian Uncertainty Assessment," Risk Analysis, John Wiley & Sons, vol. 21(4), pages 579-584, August.
    2. Greenland S., 2003. "The Impact of Prior Distributions for Uncontrolled Confounding and Response Bias: A Case Study of the Relation of Wire Codes and Magnetic Fields to Childhood Leukemia," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 47-54, January.
    3. Minh Ha‐Duong & Elizabeth A. Casman & M. Granger Morgan, 2004. "Bounding Poorly Characterized Risks: A Lung Cancer Example," Risk Analysis, John Wiley & Sons, vol. 24(5), pages 1071-1083, October.
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