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Efficient design of cluster randomized and multicentre trials with unknown intraclass correlation
Gerard J P van Breukelen1, Math J J M Candel2
1Department of Methodology and Statistics, Maastricht University, Maastricht, The Netherlands. gerard.vbreukelen@maastrichtuniversity.nl.
Statistical Methods in Medical Research
|September 23, 2011
Summary
This study introduces Maximin designs (MMDs) for cluster randomized trials, offering robust sample size calculations when intraclass correlation (ICC) is unknown. MMDs ensure good performance across various ICC values, improving efficiency and precision in trial planning.
Area of Science:
- Biostatistics
- Clinical Trials Methodology
- Health Services Research
Background:
- Sample size calculations for cluster randomized trials (CRTs) typically rely on the intraclass correlation (ICC), which is often unknown.
- Existing methods for optimal sample size determination in CRTs are sensitive to the assumed ICC, leading to potential inefficiencies if the true ICC deviates from the assumption.
Purpose of the Study:
- To develop and evaluate Maximin designs (MMDs) for CRTs that provide robust sample size recommendations across a range of plausible intraclass correlation (ICC) values.
- To offer practical guidance for determining optimal sample sizes in cluster randomized trials when the ICC is uncertain, balancing power, precision, and sampling costs.
Main Methods:
- The study proposes Maximin designs (MMDs) based on relative efficiency (RE) and overall efficiency.
- These MMDs are compared against locally optimal designs across a spectrum of potential ICC values.
- The methodology is illustrated using data from numerous primary care cluster randomized trials.
Main Results:
- Maximin designs (MMDs) demonstrate good performance over a range of intraclass correlation (ICC) values, offering improved relative efficiency compared to locally optimal designs.
- MMDs provide a balance between maximizing power and minimizing sampling costs, even when the precise ICC is unknown.
- The optimal design for an ICC value halfway through its assumed range also shows efficiency across various ICCs.
Conclusions:
- Maximin designs (MMDs) are recommended for practical application in cluster randomized trials due to their efficiency across a range of intraclass correlation (ICC) values.
- To facilitate the use of MMDs, trial reports should include information on the cost per cluster and per person.
- These findings enhance the reliability of sample size calculations in cluster randomized trials, particularly when dealing with uncertainty in ICC estimates.
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