power swgee: GEE-based power calculations in stepped wedge cluster randomized trials

Author:

Gallis John A.1,Wang Xueqi2,Rathouz Paul J.3,Preisser John S.4,Li Fan5,Turner Elizabeth L.1

Affiliation:

1. Department of Biostatistics and Bioinformatics and Duke Global Health Institute, Duke University, Durham, NC,

2. Department of Biostatistics Yale School of Public Health and Department of Internal Medicine Yale School of Medicine, New Haven, CT,

3. Department of Population Health, Dell Medical School, University of Texas at Austin, Austin, TX,

4. Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC,

5. Department of Biostatistics and Center for Methods in Implementation and Prevention Science, Yale School of Public Health, New Haven, CT,

Abstract

Stepped wedge cluster randomized trials (SW-CRTs) are increasingly being used to evaluate interventions in medical, public health, educational, and social science contexts. With the longitudinal and crossover natures of an SW-CRT, complex analysis techniques are often needed, which makes appropriately powering SW-CRTs challenging. In this article, we introduce a newly developed SW-CRT power calculator embedded within the power command in Stata. The power calculator assumes a marginal model (that is, generalized estimating equations) for the primary analysis of SW-CRTs, for which other currently available SW-CRT power calculators may not be suitable. The command accommodates complete cross-sectional and closed-cohort designs and includes multilevel correlation structures appropriate for such designs. We discuss the methods and formulas underlying our SW-CRT calculator and provide illustrative examples of the use of power swgee. We provide suggestions about the choice of parameters in power swgee and conclude by discussing areas of future research that may improve the command.

Publisher

SAGE Publications

Subject

Mathematics (miscellaneous)

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