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Admissible multiarm stepped-wedge cluster randomized trial designs

Lookup NU author(s): Dr Michael Grayling, Professor James Wason

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2018 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. Numerous publications have now addressed the principles of designing, analyzing, and reporting the results of stepped-wedge cluster randomized trials. In contrast, there is little research available pertaining to the design and analysis of multiarm stepped-wedge cluster randomized trials, utilized to evaluate the effectiveness of multiple experimental interventions. In this paper, we address this by explaining how the required sample size in these multiarm trials can be ascertained when data are to be analyzed using a linear mixed model. We then go on to describe how the design of such trials can be optimized to balance between minimizing the cost of the trial and minimizing some function of the covariance matrix of the treatment effect estimates. Using a recently commenced trial that will evaluate the effectiveness of sensor monitoring in an occupational therapy rehabilitation program for older persons after hip fracture as an example, we demonstrate that our designs could reduce the number of observations required for a fixed power level by up to 58%. Consequently, when logistical constraints permit the utilization of any one of a range of possible multiarm stepped-wedge cluster randomized trial designs, researchers should consider employing our approach to optimize their trials efficiency.


Publication metadata

Author(s): Grayling MJ, Mander AP, Wason JMS

Publication type: Article

Publication status: Published

Journal: Statistics in Medicine

Year: 2019

Volume: 38

Issue: 7

Pages: 1103-1119

Print publication date: 30/03/2019

Online publication date: 06/11/2018

Acceptance date: 10/10/2018

Date deposited: 19/11/2018

ISSN (print): 0277-6715

ISSN (electronic): 1097-0258

Publisher: John Wiley and Sons Ltd

URL: https://doi.org/10.1002/sim.8022

DOI: 10.1002/sim.8022


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