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Power calculation for cross-sectional stepped wedge cluster randomized trials with variable cluster sizes.

Linda J Harrison1, Tom Chen2, Rui Wang1,2

  • 1Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, Massachusetts.

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|October 19, 2019
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Summary

Sample size calculations for stepped wedge cluster randomized trials (SW-CRTs) must account for varying cluster sizes. Ignoring size variation reduces study power, especially with fewer clusters, impacting intervention effect estimation.

Keywords:
cluster randomized trialscluster size variationcross-sectionalpowersample sizestepped wedge

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Area of Science:

  • Biostatistics
  • Clinical Trials Methodology
  • Epidemiology

Background:

  • Standard sample size calculations for stepped wedge cluster randomized trials (SW-CRTs) assume equal cluster sizes.
  • Substantial variation in cluster sizes can lead to underpowered studies if not properly addressed.

Purpose of the Study:

  • To investigate the relative efficiency of SW-CRTs with varying cluster sizes compared to those with equal sizes.
  • To derive variance estimators for intervention effects that account for cluster size variation using mixed-effects models.

Main Methods:

  • Derived variance estimators for intervention effects under a mixed-effects model accounting for cluster size variation.
  • Developed algorithms to determine power bounds based on randomization sequences.
  • Obtained an expected power approximation considering all possible randomization sequences.
  • Provided a variance formula for scenarios with known mean and coefficient of variation of cluster sizes.

Main Results:

  • The power of a SW-CRT decreases as cluster size variation increases.
  • The impact of cluster size variation on power is most pronounced when the number of clusters is small.
  • The order of intervention in randomized sequences affects study power.

Conclusions:

  • Accurate sample size calculations for SW-CRTs require accounting for cluster size variability.
  • Ignoring cluster size variation can lead to underpowered trials and inaccurate intervention effect estimates.
  • The proposed methods provide a more robust approach to power calculations in SW-CRTs with heterogeneous cluster sizes.