Browse by author
Lookup NU author(s): Samuel Sarkodie, Professor James WasonORCiD, Dr Michael Grayling
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© The Author(s) 2022. Background/Aims: To evaluate how uncertainty in the intra-cluster correlation impacts whether a parallel-group or stepped-wedge cluster-randomized trial design is more efficient in terms of the required sample size, in the case of cross-sectional stepped-wedge cluster-randomized trials and continuous outcome data. Methods: We motivate our work by reviewing how the intra-cluster correlation and standard deviation were justified in 54 health technology assessment reports on cluster-randomized trials. To enable uncertainty at the design stage to be incorporated into the design specification, we then describe how sample size calculation can be performed for cluster- randomized trials in the ‘hybrid’ framework, which places priors on design parameters and controls the expected power in place of the conventional frequentist power. Comparison of the parallel-group and stepped-wedge cluster-randomized trial designs is conducted by placing Beta and truncated Normal priors on the intra-cluster correlation, and a Gamma prior on the standard deviation. Results: Many Health Technology Assessment reports did not adhere to the Consolidated Standards of Reporting Trials guideline of indicating the uncertainty around the assumed intra-cluster correlation, while others did not justify the assumed intra-cluster correlation or standard deviation. Even for a prior intra-cluster correlation distribution with a small mode, moderate prior densities on high intra-cluster correlation values can lead to a stepped-wedge cluster-randomized trial being more efficient because of the degree to which a stepped-wedge cluster-randomized trial is more efficient for high intra-cluster correlations. With careful specification of the priors, the designs in the hybrid framework can become more robust to, for example, an unexpectedly large value of the outcome variance. Conclusion: When there is difficulty obtaining a reliable value for the intra-cluster correlation to assume at the design stage, the proposed methodology offers an appealing approach to sample size calculation. Often, uncertainty in the intra-cluster correlation will mean a stepped-wedge cluster-randomized trial is more efficient than a parallel-group cluster-randomized trial design.
Author(s): Sarkodie SK, Wason JMS, Grayling MJ
Publication type: Article
Publication status: Published
Journal: Clinical Trials
Year: 2023
Volume: 20
Issue: 1
Pages: 59-70
Print publication date: 01/02/2023
Online publication date: 09/09/2022
Acceptance date: 02/04/2018
Date deposited: 03/10/2022
ISSN (print): 1740-7745
ISSN (electronic): 1740-7753
Publisher: SAGE Publications Ltd
URL: https://doi.org/10.1177/17407745221123507
DOI: 10.1177/17407745221123507
PubMed id: 36086822
Altmetrics provided by Altmetric
