Optimal designs for dose-response models with restricted design spaces

• 成果类型: Article
• 署名作者: Biedermann, Stefanie; Dette, Holger; Zhu, Wei
• 署名单位: Ruhr University Bochum; State University of New York (SUNY) System; Stony Brook University
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1198/016214505000001087
• 发表日期: 2006
• 页码: 747-759
• 关键词: bayesian optimal designs; nonlinear-regression models; probit; logit; EQUIVALENCE; CURVES

摘要

In close-response studies, the dose range is often restricted because of concerns over drug toxicity and/or efficacy. We derive optimal designs for estimating the underlying dose-response curve for a restricted or unrestricted dose range with respect to a broad class of optimality criteria. The underlying curve belongs to a diversified set of link functions suitable for the dose-response studies and having a common canonical form. These include the fundamental binary response models-the logit and the probit, as well as the skewed versions of these models. Our methodology is based on a new geometric interpretation of optimal designs with respect to Kiefer's Phi(p) criteria in regression models with two parameters, which is of independent interest. It provides an intuitive illustration of the number and locations of the support points of Phi(p)-optimal designs. Moreover, the geometric results generalize the classical characterization of D-optimal designs by the minimum covering ellipsoid to the class of Kiefer's Phi(p) criteria. The results are illustrated through the redesign of a dose ranging trial.