论文标题
%crtfastgeepwr:SAS宏,用于多个周期群集随机试验的广义估计方程,并应用于阶梯楔形设计
%CRTFASTGEEPWR: a SAS macro for power of the generalized estimating equations of multi-period cluster randomized trials with application to stepped wedge designs
论文作者
论文摘要
多周期群集随机试验(CRT)越来越多地用于评估小组级别提供的干预措施。虽然普遍的估计方程(GEE)通常用于提供CRT中的人群平均推断,但基于多参数,群集内相关结构的通用方法和统计软件工具的差距适用于多个Period CRT,可以适应完整和不完整的设计。描述了一种用于确定统计能力的计算快速,非仿真程序,用于完成完整且不完整的多期聚类随机试验的GEE分析。该过程是通过SAS宏,\%CRTFASTGEEPWR来实现的,该过程适用于二进制,计数和连续响应以及多个多期CRT中的几个相关结构。在边际平均模型的不同规格和集群内相关结构的不同规格下,两个完整和两个不完整的楔形楔形群集随机试验场景的功率计算中说明了SAS宏。所提出的GEE功率方法非常通用,如SAS宏所示,并具有许多输入选项。除了横截面和封闭的队列梯级楔形试验外,功率过程和宏还可以用于平行和跨界CRT的计划。
Multi-period cluster randomized trials (CRTs) are increasingly used for the evaluation of interventions delivered at the group level. While generalized estimating equations (GEE) are commonly used to provide population-averaged inference in CRTs, there is a gap of general methods and statistical software tools for power calculation based on multi-parameter, within-cluster correlation structures suitable for multi-period CRTs that can accommodate both complete and incomplete designs. A computationally fast, non-simulation procedure for determining statistical power is described for the GEE analysis of complete and incomplete multi-period cluster randomized trials. The procedure is implemented via a SAS macro, \%CRTFASTGEEPWR, which is applicable to binary, count and continuous responses and several correlation structures in multi-period CRTs. The SAS macro is illustrated in the power calculation of two complete and two incomplete stepped wedge cluster randomized trial scenarios under different specifications of marginal mean model and within-cluster correlation structure. The proposed GEE power method is quite general as demonstrated in the SAS macro with numerous input options. The power procedure and macro can also be used in the planning of parallel and crossover CRTs in addition to cross-sectional and closed cohort stepped wedge trials.