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Related Experiment Video

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Power analysis for concurrent balanced or imbalanced multiple-intervention stepped wedge design: a simulation-based

Yi Zhang1,2, Meng Zheng1,2, Xue-Zhi Liang1,2

  • 1Department of Medical Statistics, School of Public Health, Sun Yat-Sen University, Guangzhou, China.

BMC Medical Research Methodology
|April 16, 2025
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Summary

For concurrent multiple-intervention stepped wedge designs (M-SWD), imbalanced group allocation is preferred when treatment effects differ significantly, improving statistical power. Increasing cluster numbers and considering correlation parameters are key for effective M-SWD trials.

Keywords:
Power analysisSimulation-based approachStepped wedge designTrials

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Clinical Trial Design

Background:

  • The multiple-intervention stepped wedge design (M-SWD) is a widely adopted cluster randomized trial design.
  • Power analysis for concurrent balanced and imbalanced M-SWDs is crucial for efficient trial planning.

Purpose of the Study:

  • To conduct power analysis for concurrent balanced and imbalanced M-SWDs.
  • To evaluate the impact of design and correlation parameters on statistical power.

Main Methods:

  • Simulation-based power analysis using cross-sectional or closed-cohort data.
  • Examination of design parameters: cluster size and number of clusters.
  • Assessment of correlation parameters: total random effects variance (TRE), cluster autocorrelation coefficient (CAC), and individual autocorrelation coefficient (IAC).

Main Results:

  • Increasing the number of clusters enhances statistical power for a fixed total sample size.
  • Concurrent imbalanced M-SWDs offer sample size savings when treatment effects are dissimilar, with optimal allocation ratios up to 4:1.
  • Statistical power increases with decreasing TRE and increasing CAC and IAC, with autocorrelation having a more pronounced effect at larger values.

Conclusions:

  • Concurrent imbalanced M-SWDs are preferable to balanced designs when treatment effects are substantially different (allocation ratio ≤ 4:1).
  • For both balanced and imbalanced M-SWDs, utilizing a large number of smaller clusters is recommended.
  • Careful consideration of correlation parameter estimates is vital during trial design for both M-SWD variants.