Admissible multiarm stepped-wedge cluster randomized trial designs
Admissible multiarm stepped-wedge cluster randomized trial designs
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DOI：
10.1002/sim.8022
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发表时间：
2019-03-30
影响因子：
2
通讯作者：
Wason, James M. S.
中科院分区：
文献类型：
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作者：
Grayling, Michael J.;Mander, Adrian P.;Wason, James M. S.
许多出版物现在已经讨论了设计、分析和报告阶梯楔形群随机试验的结果的原则。相比之下，很少有关于设计和分析多臂阶梯形楔形群随机试验的研究，这些试验用于评估多种实验干预的有效性。在这篇文章中，我们通过解释在使用线性混合模型分析数据时如何确定这些多臂试验中所需的样本量来解决这一问题。然后，我们继续描述如何优化此类试验的设计，以在最小化试验成本和最小化治疗效果估计的协方差矩阵的某些函数之间取得平衡。以最近开始的一项试验为例，该试验将评估传感器监测在髋部骨折后老年人职业治疗康复计划中的有效性，我们证明我们的设计可以将固定功率水平所需的观察次数减少高达58%。因此，当后勤限制允许使用一系列可能的多臂阶梯楔形群随机试验设计中的任何一种时，研究人员应该考虑使用我们的方法来优化他们的试验效率。
Numerous publications have now addressed the principles of designing, analyzing, and reporting the results of stepped-wedge cluster randomized trials. In contrast, there is little research available pertaining to the design and analysis of multiarm stepped-wedge cluster randomized trials, utilized to evaluate the effectiveness of multiple experimental interventions. In this paper, we address this by explaining how the required sample size in these multiarm trials can be ascertained when data are to be analyzed using a linear mixed model. We then go on to describe how the design of such trials can be optimized to balance between minimizing the cost of the trial and minimizing some function of the covariance matrix of the treatment effect estimates. Using a recently commenced trial that will evaluate the effectiveness of sensor monitoring in an occupational therapy rehabilitation program for older persons after hip fracture as an example, we demonstrate that our designs could reduce the number of observations required for a fixed power level by up to 58%. Consequently, when logistical constraints permit the utilization of any one of a range of possible multiarm stepped-wedge cluster randomized trial designs, researchers should consider employing our approach to optimize their trials efficiency.