Orthogonal array composite designs for drug combination experiments with applications for tuberculosis
Orthogonal array composite designs for drug combination experiments with applications for tuberculosis
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DOI：
10.1002/sim.9423
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发表时间：
2022-05-06
影响因子：
2
通讯作者：
Wong，Weng Kee
中科院分区：
文献类型：
--
作者：
Luna，Jose;Jaynes，Jessica;Wong，Weng Kee
本文的目的是提供正交组合设计（OACD）方法的概述，说明各种优势，并提供真实的世界的应用。OACD将两水平析因设计与三水平正交表相结合，可用作构建响应面模型的现有复合设计的替代方案。我们比较了OACD相对于常用的中心复合设计（CCD）的D$$ D $$-效率，当有一些缺失的观察结果，并证明OACD是更强大的缺失观察两种情况。第一种情况假设来自一个阶乘点或一个附加点的一个缺失观测。第二种情况假设两个缺失观测来自两个阶乘点或两个附加点，或者来自一个阶乘点和一个附加点。此外，我们比较了OACD和CCD在I$$ I $$-最优性方面的精确预测。最后，提供了OACD在结核病药物联合研究中的真实的应用。
The aim of this article is to provide an overview of the orthogonal array composite design (OACD) methodology, illustrate the various advantages, and provide a real‐world application. An OACD combines a two‐level factorial design with a three‐level orthogonal array and it can be used as an alternative to existing composite designs for building response surface models. We compare the D$$ D $$‐efficiencies of OACDs relative to the commonly used central composite design (CCD) when there are a few missing observations and demonstrate that OACDs are more robust to missing observations for two scenarios. The first scenario assumes one missing observation either from one factorial point or one additional point. The second scenario assumes two missing observations either from two factorial points or from two additional points, or from one factorial point and one additional point. Furthermore, we compare OACDs and CCDs in terms of I$$ I $$‐optimality for precise predictions. Lastly, a real‐world application of an OACD for a tuberculosis drug combination study is provided.