Robust and efficient designs for the Michaelis-Menten model

• 成果类型: Article
• 署名作者: Dette, H; Biedermann, S
• 署名单位: Ruhr University Bochum
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1198/016214503000000585
• 发表日期: 2003
• 页码: 679-686
• 关键词: hormone-receptor assays; linear-models; parameters; enzyme

摘要

For the Michaelis-Menten model, we determine designs that maximize the minimum of the D-efficiencies over a certain interval for the nonlinear parameter. The best two point designs can be found explicitly, and a characterization is given when these designs are optimal within the class of all designs. In most cases of practical interest, the determined designs are highly efficient and robust with respect to misspecification of the nonlinear parameter. The results are illustrated and applied in an example of a hormone receptor assay.