Modeling and identifying optimum designs for fitting dose-response curves based on raw optical density data

• 成果类型: Article
• 署名作者: Hedayat, AS; Yan, B; Pezzuto, JM
• 署名单位: University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.2307/2965578
• 发表日期: 1997
• 页码: 1132-1140
• 关键词: binary data

摘要

For raw optical density (ROD) data, such as those generated in biological assays using a 96-well plate reader, D-optimal designs are identified for a family of homogeneous nonlinear models with two parameters developed for fitting and studying dose-response curves. Further, within the class of k-point equally spaced and uniform designs, D-optimal designs are specified. Also, the D-efficiency of the D-optimal equally spaced and uniform k-point designs are compared to D-optimal design for 3 less than or equal to k less than or equal to 7. The efficiency robustness of these optimal designs with respect to initial nominal values of the parameters are investigated. In addition, D-optimal designs are derived for a family of heterogeneous nonlinear models.