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

IF 1.2 4区 数学
Seung Won Hyun, W. Wong
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引用次数: 10

Abstract

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.
剂量响应函数和感兴趣剂量水平研究的多目标优化设计
我们构建了一个优化设计,以同时估计剂量发现试验中三个共同的有趣特征,每个特征的重点可能不同。这些特征是(1)剂量-反应曲线的形状,(2)中位有效剂量和(3)最小有效剂量水平。这项任务的一个主要困难是,针对单个目标的最佳设计可能不适用于其他目标。文献中有针对双目标的最佳设计,但我们无法找到针对3个或更多目标的最佳设计。原因在于,寻找双目标优化设计的方法并不适用于3个或更多的多目标设计问题。我们提出了一种寻找多目标优化设计的方法,该方法估计了三个特征,对于更重要的目标,用户指定的效率更高。我们使用灵活的四参数逻辑模型来说明方法,但我们的方法适用于寻找其他类型的目标和模型的多目标优化设计。我们还研究了多目标优化设计在标称参数值错误规范和最优性准则变化时的鲁棒性。我们还提供了生成量身定制的多目标优化设计的计算机代码。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Biostatistics
International Journal of Biostatistics Mathematics-Statistics and Probability
CiteScore
2.30
自引率
8.30%
发文量
28
期刊介绍: The International Journal of Biostatistics (IJB) seeks to publish new biostatistical models and methods, new statistical theory, as well as original applications of statistical methods, for important practical problems arising from the biological, medical, public health, and agricultural sciences with an emphasis on semiparametric methods. Given many alternatives to publish exist within biostatistics, IJB offers a place to publish for research in biostatistics focusing on modern methods, often based on machine-learning and other data-adaptive methodologies, as well as providing a unique reading experience that compels the author to be explicit about the statistical inference problem addressed by the paper. IJB is intended that the journal cover the entire range of biostatistics, from theoretical advances to relevant and sensible translations of a practical problem into a statistical framework. Electronic publication also allows for data and software code to be appended, and opens the door for reproducible research allowing readers to easily replicate analyses described in a paper. Both original research and review articles will be warmly received, as will articles applying sound statistical methods to practical problems.
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