Testing for additivity in chemical mixtures using a fixed-ratio ray design and statistical equivalence testing methods

Le Anna G. Stork, Chris Gennings, Walter H. Carter, Robert E. Johnson, Darcy P. Mays, Jane Ellen Simmons, Elizabeth D. Wagner, Michael J. Plewa

Research output: Contribution to journalArticlepeer-review

Abstract

Fixed-ratio ray designs have been used for detecting and characterizing interactions of large numbers of chemicals in combination. Single-chemical dose-response data are used to predict an "additivity curve" along an environmentally relevant ray. A "mixture curve" is estimated from the mixture dose-response data along the ray. A test of additivity is equivalent to a test of coincidence of these two curves, which is based on the traditional hypothesis testing framework that assumes additivity in the null hypothesis and rejects with evidence of interaction. However, failure to reject may be due to lack of statistical power, making the claim of additivity problematic. As a solution we have developed rigorous methodology to test for additivity using statistical equivalence testing logic in which additivity is claimed based on pre-specified biologically important additivity margins, if the data support such a claim. Using the principle of confidence interval inclusion, a confidence region about the difference of meaningful functions of model parameters from the mixture model and that predicted under additivity is computed. When the confidence region is completely contained within the additivity margins then additivity is claimed with a Type I error rate chosen a priori to be some acceptably small value. The method is illustrated using an environmentally relevant fixed-ratio mixture of nine haloacetic acids where cytotoxic response is measured.

Original languageEnglish (US)
Pages (from-to)514-533
Number of pages20
JournalJournal of Agricultural, Biological, and Environmental Statistics
Volume12
Issue number4
DOIs
StatePublished - Dec 1 2007

Keywords

  • Antagonism
  • Enhanced toxicity
  • Risk assessment
  • Synergism

ASJC Scopus subject areas

  • Statistics and Probability
  • Agricultural and Biological Sciences (miscellaneous)
  • Environmental Science(all)
  • Agricultural and Biological Sciences(all)
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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