A general method for calculating power for GEE analysis of complete and incomplete stepped wedge cluster randomized trials

Author:

Zhang Ying1ORCID,Preisser John S1,Turner Elizabeth L2ORCID,Rathouz Paul J3,Toles Mark4,Li Fan56ORCID

Affiliation:

1. Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA

2. Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA

3. Department of Population Health, The University of Texas at Austin, Austin, TX, USA

4. School of Nursing, University of North Carolina, Chapel Hill, NC, USA

5. Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA

6. Center for Methods in Implementation and Prevention Science, Yale School of Public Health, New Haven, CT, USA

Abstract

Stepped wedge designs have uni-directional crossovers at randomly assigned time points (steps) where clusters switch from control to intervention condition. Incomplete stepped wedge designs are increasingly used in cluster randomized trials of health care interventions and have periods without data collection due to logistical, resource and patient-centered considerations. The development of sample size formulae for stepped wedge trials has primarily focused on complete designs and continuous responses. Addressing this gap, a general, fast, non-simulation based power procedure is proposed for generalized estimating equations analysis of complete and incomplete stepped wedge designs and its predicted power is compared to simulated power for binary and continuous responses. An extensive set of simulations for six and twelve clusters is based upon the Connect-Home trial with an incomplete stepped wedge design. Results show that empirical test size is well controlled using a t-test with bias-corrected sandwich variance estimator for as few as six clusters. Analytical power agrees well with a simulated power in scenarios with twelve clusters. For six clusters, analytical power is similar to simulated power with estimation using the correctly specified model-based variance estimator. To explore the impact of study design choice on power, the proposed fast GEE power method is applied to the Connect-Home trial design, four alternative incomplete stepped wedge designs and one complete design.

Funder

Patient-Centered Outcomes Research Institute

Publisher

SAGE Publications

Subject

Health Information Management,Statistics and Probability,Epidemiology

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