Abstract

Optimal design of multisite randomized trials leverages sampling costs to optimize sampling ratios and ultimately identify more efficient and powerful designs. Past implementations of the optimal design framework have assumed that costs of sampling units are equal across treatment conditions. In this study, we developed a more flexible optimal design framework by introducing additional optimal design parameters that track sampling cost variation across levels and treatment conditions. The proposed framework can frequently suggest more powerful and efficient designs than those identified by conventional frameworks. Additionally, the more flexible framework allows researchers to place constraints for practical considerations. The proposed method has been implemented in the R package odr.

摘要

多中心随机试验的优化设计利用抽样成本来优化抽样比率并最终确定更有效和更强大的设计。最佳设计框架的过去实施假设采样单元的成本在不同处理条件下是相等的。在这项研究中，我们通过引入额外的优化设计参数开发了一个更灵活的优化设计框架，这些参数跟踪不同水平和处理条件的采样成本变化。所提出的框架通常可以提出比传统框架所确定的更强大和更有效的设计。此外，更灵活的框架允许研究人员为实际考虑设置约束。建议的方法已在 R 包odr中实现。