Arbeitspapier
Optimal designs for dose finding experiments in toxicity studies
We construct optimal designs for estimating fetal malformation rate, prenatal death rate and an overall toxicity index in a toxicology study under a broad range of model assumptions. We use Weibull distributions to model these rates and assume that the number of implants depend on the dose level. We study properties of the optimal designs when the intra-litter correlation coefficient depends on the dose levels in different ways. Locally optimal designs are found, along with robustified versions of the designs that are less sensitive to mis-specification in the nominal values of the model parameters. We also report e?ciencies of commonly used designs in toxicological experiments and efficiencies of the proposed optimal designs when the true rates have non-Weibull distributions. Optimal design strategies for ?nding multiple-objective designs in toxicology studies are outlined as well.
- Language
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Englisch
- Bibliographic citation
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Series: Technical Report ; No. 2008,09
- Subject
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Weibull model, dose finding experiment
locally co-optimal design
multipleobjective design
robust optimal design
- Event
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Geistige Schöpfung
- (who)
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Dette, Holger
Pepelyshev, Andrey
Wong, Weng Kee
- Event
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Veröffentlichung
- (who)
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Technische Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
- (where)
-
Dortmund
- (when)
-
2008
- Handle
- Last update
-
10.03.2025, 11:44 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Dette, Holger
- Pepelyshev, Andrey
- Wong, Weng Kee
- Technische Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
Time of origin
- 2008
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Optimal designs for estimating the interesting part of a dose-effect curve
Optimal experimental designs for inverse quadratic regression models
Canonical moments, orthogonal polynomials with application to statistics
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