Original Article
Stepped wedge designs could reduce the required sample size in cluster randomized trials

https://doi.org/10.1016/j.jclinepi.2013.01.009Get rights and content
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Abstract

Objective

The stepped wedge design is increasingly being used in cluster randomized trials (CRTs). However, there is not much information available about the design and analysis strategies for these kinds of trials. Approaches to sample size and power calculations have been provided, but a simple sample size formula is lacking. Therefore, our aim is to provide a sample size formula for cluster randomized stepped wedge designs.

Study Design and Setting

We derived a design effect (sample size correction factor) that can be used to estimate the required sample size for stepped wedge designs. Furthermore, we compared the required sample size for the stepped wedge design with a parallel group and analysis of covariance (ANCOVA) design.

Results

Our formula corrects for clustering as well as for the design. Apart from the cluster size and intracluster correlation, the design effect depends on choices of the number of steps, the number of baseline measurements, and the number of measurements between steps. The stepped wedge design requires a substantial smaller sample size than a parallel group and ANCOVA design.

Conclusion

For CRTs, the stepped wedge design is far more efficient than the parallel group and ANCOVA design in terms of sample size.

Keywords

Cluster randomized trial
Stepped wedge design
Parallel group design
ANCOVA
Sample size
Design effect

Cited by (0)

Conflict of interest: Neither the article nor any parts of it have been published or submitted before. No external funding has been received and no conflict of interest is present.

1

W.W and E.de.H. are the joint contributions.