ArticleStatistics in medicine2019
Admissible multiarm stepped-wedge cluster randomized trial designs.
Article in Statistics in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Clinical Trial Simulation: Planning With the OCTAVE Framework, Implementation and Validation Principles.Statistics in medicine · 2026Article
- Identifying Less Burdensome and More Cost-Efficient Incomplete Stepped Wedge Designs for Continuous Outcomes Collected via Repeated Cross-Sections.Statistics in medicine · 2025Article
- Mixed-effects models for the design and analysis of stepped wedge cluster randomized trials: An overview.Statistical methods in medical research · 2021Review
- The hunt for efficient, incomplete designs for stepped wedge trials with continuous recruitment and continuous outcome measures.BMC medical research methodology · 2020Article
- Admissible multiarm stepped-wedge cluster randomized trial designs.Statistics in medicine · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
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.
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Registered trials
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