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Does it decay? Obtaining decaying correlation parameter values from previously analysed cluster randomised trials.

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Summary
This summary is machine-generated.

Cluster randomized trials often assume equal intracluster correlation. This study shows how to use existing correlation estimates to model decaying correlations, improving study power and accuracy.

Keywords:
Cluster autocorrelationhierarchical modelsintracluster correlationsample size calculationstepped wedgewithin-cluster correlation structure

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Area of Science:

  • Biostatistics
  • Clinical Trials
  • Epidemiology

Background:

  • Cluster randomized trials (CRTs) commonly assume constant intracluster correlation (ICC) for all participant pairs within a cluster.
  • This assumption may be violated if correlation decays over time between measurements.
  • Ignoring correlation decay can lead to underpowered studies and inaccurate confidence intervals for treatment effects.

Purpose of the Study:

  • To demonstrate how to derive plausible decaying correlation structures from existing ICC estimates.
  • To provide guidance for researchers planning CRTs, particularly when correlation decay is suspected but not modeled.
  • To develop practical tools for assessing the impact of decaying correlations on sample size and power calculations.

Main Methods:

  • Utilized intracluster correlation (ICC) estimates from linear mixed models with exchangeable or block-exchangeable structures.
  • Developed methods to infer decaying correlation values from standard ICC estimates that omit decay.
  • Presented an online application to facilitate the estimation of decaying correlations for trial planning.

Main Results:

  • Showed that ICC values from models assuming no decay can inform plausible decaying correlation structures.
  • Demonstrated a method to obtain estimates of decaying correlations from standard ICC estimates.
  • An accessible online tool is available for researchers to explore the impact of decaying correlations.

Conclusions:

  • It is feasible to derive meaningful decaying correlation parameters from standard ICC estimates.
  • This approach allows for more accurate sample size and power calculations in CRTs where correlation decay is a concern.
  • The developed methods and tool aid in robust trial design and analysis by accounting for temporal correlation decay.