Blinded and unblinded sample size re-estimation procedures for stepped-wedge cluster randomized trials
Michael Grayling, Adrian Mander, James Wason

TL;DR
This paper introduces blinded and unblinded sample size re-estimation methods for stepped-wedge cluster randomized trials, improving power when initial variance estimates are inaccurate.
Contribution
It proposes new SSRE procedures for SW-CRTs, including blinded estimators and performance analysis, enhancing trial efficiency.
Findings
SSRE increased power by up to 29% when variance was under-specified.
Performance was insensitive to timing of interim assessments.
Procedures are practical and can be incorporated into future SW-CRTs.
Abstract
The ability to accurately estimate the sample size required by a stepped-wedge (SW) cluster randomized trial (CRT) routinely depends upon the specification of several nuisance parameters. If these parameters are mis-specified, the trial could be over-powered, leading to increased cost, or under-powered, enhancing the likelihood of a false negative. We address this issue here for cross-sectional SW-CRTs, analyzed with a particular linear mixed model, by proposing methods for blinded and unblinded sample size re-estimation (SSRE). Blinded estimators for the variance parameters of a SW-CRT analyzed using the Hussey and Hughes model are derived. Then, procedures for blinded and unblinded SSRE after any time period in a SW-CRT are detailed. The performance of these procedures is then examined and contrasted using two example trial design scenarios. We find that if the two key variance…
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