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Adjusting for mortality effects in chronic toxicity testing: Mixture model approach

Authors

  • Shin Cheng David Wang,

    1. Statistics Department, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061-0439, USA
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  • Eric P. Smith

    Corresponding author
    1. Statistics Department, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061-0439, USA
    • Statistics Department, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061-0439, USA
    Search for more papers by this author

Abstract

Chronic toxicity tests, such as the Ceriodaphnia dubia 7-d test are typically analyzed using standard statistical methods such as analysis of variance or regression. Recent research has emphasized the use of Poisson regression or more generalized regression for the analysis of the fecundity data from these studies. A possible problem in using standard statistical techniques is that mortality may occur from toxicant effects as well as reduced fecundity. A mixture model that accounts for fecundity and mortality is proposed for the analysis of data arising from these studies. Inferences about key parameters in the model are discussed. A joint estimate of the inhibition concentration is proposed based on the model. Confidence interval estimation via the bootstrap method is discussed. An example is given for a study involving copper and mercury.

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