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Confidence limits on one-stage model parameters in benchmark risk assessment

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Abstract

In modern environmental risk analysis, inferences are often desired on those low dose levels at which a fixed benchmark risk is achieved. In this paper, we study the use of confidence limits on parameters from a simple one-stage model of risk historically popular in benchmark analysis with quantal data. Based on these confidence bounds, we present methods for deriving upper confidence limits on extra risk and lower bounds on the benchmark dose. The methods are seen to extend automatically to the case where simultaneous inferences are desired at multiple doses. Monte Carlo evaluations explore characteristics of the parameter estimates and the confidence limits under this setting.

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Authors and Affiliations

  1. Department of Mathematics, Northern Kentucky University, Highland Heights, KY, 41099, USA

    Brooke E. Buckley

  2. Department of Mathematics, BIO5 Institute, University of Arizona, Tucson, AZ, 85721, USA

    Walter W. Piegorsch

  3. Department of Statistics, 3143 TAMU, Texas A&M University, College Station, TX, 77843, USA

    R. Webster West

Authors
  1. Brooke E. Buckley
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  2. Walter W. Piegorsch
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  3. R. Webster West
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Corresponding author

Correspondence to Brooke E. Buckley.

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Buckley, B.E., Piegorsch, W.W. & West, R.W. Confidence limits on one-stage model parameters in benchmark risk assessment. Environ Ecol Stat 16, 53–62 (2009). https://doi.org/10.1007/s10651-007-0076-2

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  • DOI: https://doi.org/10.1007/s10651-007-0076-2

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