Blinded and unblinded sample size re-estimation procedures for stepped-wedge cluster randomized trials
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 parameters were under-specified by 50%, the SSRE procedures were able to increase power over the conventional SW-CRT design by up to 29%, resulting in an empirical power above the desired level. Moreover, the performance of the re-estimation procedures was relatively insensitive to the timing of the interim assessment. Thus, the considered SSRE procedures can bring substantial gains in power when the underlying variance parameters are mis-specified. Though there are practical issues to consider, the procedure's performance means researchers should consider incorporating SSRE in to future SW-CRTs.
Cite
@article{arxiv.1710.02683,
title = {Blinded and unblinded sample size re-estimation procedures for stepped-wedge cluster randomized trials},
author = {Michael Grayling and Adrian Mander and James Wason},
journal= {arXiv preprint arXiv:1710.02683},
year = {2017}
}