School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
Stat Med. 2021 Mar 30;40(7):1736-1751. doi: 10.1002/sim.8867. Epub 2021 Jan 12.
In practice, stepped wedge trials frequently include clusters of differing sizes. However, investigations into the theoretical aspects of stepped wedge designs have, until recently, typically assumed equal numbers of subjects in each cluster and in each period. The information content of the cluster-period cells, clusters, and periods of stepped wedge designs has previously been investigated assuming equal cluster-period sizes, and has shown that incomplete stepped wedge designs may be efficient alternatives to the full stepped wedge. How this changes when cluster-period sizes are not equal is unknown, and we investigate this here. Working within the linear mixed model framework, we show that the information contributed by design components (clusters, sequences, and periods) does depend on the sizes of each cluster-period. Using a particular trial that assessed the impact of an individual education intervention on log-length of stay in rehabilitation units, we demonstrate how strongly the efficiency of incomplete designs depends on which cells are excluded: smaller incomplete designs may be more powerful than alternative incomplete designs that include a greater total number of participants. This also serves to demonstrate how the pattern of information content can be used to inform a set of incomplete designs to be considered as alternatives to the complete stepped wedge design. Our theoretical results for the information content can be extended to a broad class of longitudinal (ie, multiple period) cluster randomized trial designs.
在实践中，阶梯式楔形试验通常包括不同大小的簇。然而，直到最近，对阶梯式设计理论方面的研究通常假设每个簇和每个时期的受试者数量相等。以前，已经在假设每个簇-时期大小相等的情况下研究了阶梯式楔形设计的簇-时期单元、簇和时期的信息量，并表明不完全的阶梯式楔形设计可能是完整的阶梯式楔形设计的有效替代方案。当簇-时期大小不相等时，这种情况会如何变化尚不清楚，我们在这里对此进行了研究。在线性混合模型框架内，我们表明设计组件（簇、序列和时期）贡献的信息量确实取决于每个簇-时期的大小。使用评估个体教育干预对康复单元日志停留时间影响的特定试验，我们展示了不完全设计的效率在很大程度上取决于排除哪些单元：较小的不完全设计可能比包含更多参与者的替代不完全设计更强大。这也说明了如何使用信息量的模式来为一组要考虑的不完全设计提供信息，作为完整阶梯式楔形设计的替代方案。我们对信息量的理论结果可以扩展到广泛的纵向（即多个时期）集群随机试验设计类别。
