Multiplicity-adjusted inferences in risk assessment: Benchmark analysis with continuous response data

Yuping Wu, Walter W. Piegorsch, R. Webster West, Dengfang Tang, Maureen O. Petkewich, Wei Pan

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


We develop and study multiplicity adjustments for low-dose inferences in environmental risk assessment. Application is intended for risk analysis studies where human, animal, or ecological data are used to set safe levels of a hazardous environmental agent. A modern method for making inferences in this setting is known as benchmark analysis, where attention centers on the dose at which a fixed benchmark level of risk is achieved. Both upper confidence limits on the risk and lower confidence limits on the "benchmark dose" are of interest. In practice, a number of possible benchmark risks may be under study; if so, corrections must be applied to adjust the limits for multiplicity. In this note, we discuss approaches for doing so with continuous, nonquantal response data.

Original languageEnglish (US)
Pages (from-to)125-141
Number of pages17
JournalEnvironmental and Ecological Statistics
Issue number1
StatePublished - Mar 2006


  • Benchmark dose
  • Environmental risk analysis
  • Nonquantal dose response
  • Quantitative risk assessment
  • Simultaneous inferences

ASJC Scopus subject areas

  • Statistics and Probability
  • General Environmental Science
  • Statistics, Probability and Uncertainty


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