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Compound Optimal Designs for Percentile Estimation in Dose-Response Models with Restricted Design Intervals

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  • Dette, Holger
  • Biedermann, Stefanie
  • Zhu, Wei

Abstract

In dose-response studies, the dose range is often restricted due to ethics concerns over drug toxicity and/or efficacy, particularly when human subjects are involved. We present locally optimal designs for the estimation of several percentiles simultaneously on restricted as well as unrestricted design intervals. Our results are applicable to most of the commonly applied link functions with respect to the model under consideration. This work is a generalization of Dai (2000) where he showed that the same results hold for the logit model using Elfving?s approach on trace optimal design (Elfving, 1952).

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  • Dette, Holger & Biedermann, Stefanie & Zhu, Wei, 2005. "Compound Optimal Designs for Percentile Estimation in Dose-Response Models with Restricted Design Intervals," Technical Reports 2005,02, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    • Handle: RePEc:zbw:sfb475:200502
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    References listed on IDEAS

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    1. Linda M. Haines & Inna Perevozskaya & William F. Rosenberger, 2003. "Bayesian Optimal Designs for Phase I Clinical Trials," Biometrics, The International Biometric Society, vol. 59(3), pages 591-600, September.
    2. Dette, Holger & Biedermann, Stefanie & Zhu, Wei, 2004. "Optimal designs for dose-response models with restricted design spaces," Technical Reports 2004,40, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    3. Holger Dette, 1997. "Designing Experiments with Respect to ‘Standardized’ Optimality Criteria," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 59(1), pages 97-110.
    4. Dette, Holger & Biedermann, Stefanie & Pepelyshev, Andrey, 2004. "Some robust design strategies for percentile estimation in binary response models," Technical Reports 2004,19, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
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