CRTFASTGEEPWR: A SAS Macro for Power of Generalized Estimating Equations Analysis of Multi-Period Cluster Randomized Trials with Application to Stepped Wedge Designs - Ying Zhang; John S. Preisser; Fan Li; Elizabeth L. Turner; Paul J. Rathouz (Journal of Statistical Software)
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, nonsimulation 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.