The reduced efficiency of the cluster randomized trial design may be compensated by implementing a multi-period design. The trial then becomes longitudinal, with a risk of intermittently missing observations and dropout. This paper studies the effect of missing data on design efficiency in trials where the periods are the days of the week and clusters are followed for at least one week. The multilevel model with a decaying correlation structure is used to relate outcome to period and treatment condition. The variance of the treatment effect estimator is used to measure efficiency. When there is no data loss, efficiency increases with increasing number of subjects per day and number of weeks. Different weekly measurement schemes are used to evaluate the impact of planned missing data designs: the loss of efficiency due to measuring on fewer days is largest for few subjects per day and few weeks. Dropout is modeled by the Weibull survival function. The loss of efficiency due to dropout increases when more clusters drop out during the course of the trial, especially if the risk of dropout is largest at the beginning of the trial. The largest loss is observed for few subjects per day and a large number of weeks. An example of the effect of waiting room environments in reducing stress in dental care shows how different design options can be compared. An R Shiny app allows researchers to interactively explore various design options and to choose the best design for their trial.

整群随机试验设计的效率降低可以通过实施多期设计来补偿。然后，试验变成纵向的，有间歇性缺失观察和辍学的风险。本文研究了在试验中缺失数据对设计效率的影响，其中周期是一周中的几天，并且至少跟踪集群一周。具有衰减相关结构的多级模型用于将结果与时期和治疗条件相关联。治疗效果估计量的方差用于衡量效率。当没有数据丢失时，效率会随着每天受试者数量和周数的增加而提高。不同的每周测量方案用于评估计划的缺失数据设计的影响：对于每天和几周的少数受试者来说，由于在更少的天数上测量而导致的效率损失最大。Dropout 由 Weibull 生存函数建模。当在试验过程中更多的集群退出时，由于退出导致的效率损失会增加，特别是如果退出的风险在试验开始时最大。每天少数受试者和大量周观察到最大的损失。候诊室环境在减轻牙科护理压力方面的作用示例显示了如何比较不同的设计选项。R Shiny 应用程序允许研究人员以交互方式探索各种设计选项，并为他们的试验选择最佳设计。当在试验过程中更多的集群退出时，由于退出导致的效率损失会增加，特别是如果退出的风险在试验开始时最大。每天少数受试者和大量周观察到最大的损失。候诊室环境在减轻牙科护理压力方面的作用示例显示了如何比较不同的设计选项。R Shiny 应用程序允许研究人员以交互方式探索各种设计选项，并为他们的试验选择最佳设计。当在试验过程中更多的集群退出时，由于退出导致的效率损失会增加，特别是如果退出的风险在试验开始时最大。每天少数受试者和大量周观察到最大的损失。候诊室环境在减轻牙科护理压力方面的作用示例显示了如何比较不同的设计选项。R Shiny 应用程序允许研究人员以交互方式探索各种设计选项，并为他们的试验选择最佳设计。候诊室环境在减轻牙科护理压力方面的作用示例显示了如何比较不同的设计选项。R Shiny 应用程序允许研究人员以交互方式探索各种设计选项，并为他们的试验选择最佳设计。候诊室环境在减轻牙科护理压力方面的作用示例显示了如何比较不同的设计选项。R Shiny 应用程序允许研究人员以交互方式探索各种设计选项，并为他们的试验选择最佳设计。