Multiple-Objective Optimal Designs for Studying the Dose Response Function and Interesting Dose Levels

Hyun Seung Won () and Wong Weng Kee ()
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Hyun Seung Won: Department of Statistics, North Dakota State University, Fargo, ND 58102, USA
Wong Weng Kee: Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, USA

The International Journal of Biostatistics, 2015, vol. 11, issue 2, 253-271

Abstract: We construct an optimal design to simultaneously estimate three common interesting features in a dose-finding trial with possibly different emphasis on each feature. These features are (1) the shape of the dose-response curve, (2) the median effective dose and (3) the minimum effective dose level. A main difficulty of this task is that an optimal design for a single objective may not perform well for other objectives. There are optimal designs for dual objectives in the literature but we were unable to find optimal designs for 3 or more objectives to date with a concrete application. A reason for this is that the approach for finding a dual-objective optimal design does not work well for a 3 or more multiple-objective design problem.We propose a method for finding multiple-objective optimal designs that estimate the three features with user-specified higher efficiencies for the more important objectives. We use the flexible 4-parameter logistic model to illustrate the methodology but our approach is applicable to find multiple-objective optimal designs for other types of objectives and models. We also investigate robustness properties of multiple-objective optimal designs to mis-specification in the nominal parameter values and to a variation in the optimality criterion. We also provide computer code for generating tailor made multiple-objective optimal designs.

Keywords: approximate design; c-optimal design; compound optimal design; constrained optimal design; design efficiency; dose-finding study (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1515/ijb-2015-0044

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