%CRTFASTGEEPWR: a SAS macro for power of the generalized estimating equations 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

TL;DR
This paper introduces a fast, non-simulation SAS macro for calculating statistical power in multi-period cluster randomized trials using GEE, accommodating various response types and correlation structures.
Contribution
The paper presents a novel, computationally efficient SAS macro for power calculation in multi-period CRTs with complex correlation structures, filling a gap in existing methods.
Findings
Macro applicable to binary, count, and continuous responses
Demonstrated in power calculations for stepped wedge CRT scenarios
Flexible for complete and incomplete trial designs
Abstract
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…
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Taxonomy
TopicsStatistical Methods and Bayesian Inference · Statistical Methods in Clinical Trials · Advanced Causal Inference Techniques
