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Optimal designs for estimating critical effective dose under model uncertainty in a dose response study

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  • Dette, Holger
  • Pepelyshev, Andrey
  • Shpilev, Piter
  • Wong, Weng Kee

Abstract

Toxicologists have been increasingly using a class of models to describe a continuous response in the last few years. This class consists of nested nonlinear models and is used for estimating various parameters in the models or some meaningful function of the model parameters. Our work here is the first to address design issues for this popular class of models among toxicologists. Specifically we construct a variety of optimal designs under model uncertainty and study their properties for estimating the critical effective dose (CED), which is model dependent. Two types of optimal designs are proposed: one type maximizes the minimum of efficiencies for estimating the CED regardless which member in the class of models is the appropriate model, and (ii) dual-objectives optimal design that simultaneously selects the most appropriate model and provide the best estimates for CED at the same time. We compare relative efficiencies of these optimal designs and other commonly used designs for estimating CED. To facilitate use of these designs, we have constructed a website that practitioners can generate tailor-made designs for their settings.

Suggested Citation

  • Dette, Holger & Pepelyshev, Andrey & Shpilev, Piter & Wong, Weng Kee, 2009. "Optimal designs for estimating critical effective dose under model uncertainty in a dose response study," Technical Reports 2009,09, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    • Handle: RePEc:zbw:sfb475:200909
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    References listed on IDEAS

    as
    1. Dette, Holger & Melas, Viatcheslav B. & Wong, Weng Kee, 2005. "Optimal Design for Goodness-of-Fit of the MichaelisMenten Enzyme Kinetic Function," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1370-1381, December.
    2. W. Slob & M. N. Pieters, 1998. "A Probabilistic Approach for Deriving Acceptable Human Intake Limits and Human Health Risks from Toxicological Studies: General Framework," Risk Analysis, John Wiley & Sons, vol. 18(6), pages 787-798, December.
    3. Mirjam Moerbeek & Aldert H. Piersma & Wout Slob, 2004. "A Comparison of Three Methods for Calculating Confidence Intervals for the Benchmark Dose," Risk Analysis, John Wiley & Sons, vol. 24(1), pages 31-40, February.
    4. Dette, Holger & Pepelyshev, Andrey & Wong, Weng Kee, 2008. "Optimal designs for dose finding experiments in toxicity studies," Technical Reports 2008,09, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    5. Dette, Holger & Bretz, Frank & Pepelyshev, Andrey & Pinheiro, José, 2008. "Optimal Designs for Dose-Finding Studies," Journal of the American Statistical Association, American Statistical Association, vol. 103(483), pages 1225-1237.
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