The impact of varying cluster size in cross-sectional stepped-wedge cluster randomised trials
Autor: | Karla Hemming, Alan Girling, James Martin |
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Jazyk: | angličtina |
Rok vydání: | 2019 |
Předmět: |
Mixed model
Endpoint Determination Epidemiology Cluster randomised trials Health Informatics Design effect 03 medical and health sciences 0302 clinical medicine Outcome Assessment Health Care Statistics Cluster (physics) Range (statistics) Cluster Analysis Humans Computer Simulation 030212 general & internal medicine Cluster analysis Varying cluster size Randomized Controlled Trials as Topic Mathematics lcsh:R5-920 030503 health policy & services Small number Reproducibility of Results Stepped-wedge Cross-Sectional Studies Efficiency Research Design Sample size determination Data Interpretation Statistical Sample Size 0305 other medical science lcsh:Medicine (General) Algorithms Research Article |
Zdroj: | BMC Medical Research Methodology, Vol 19, Iss 1, Pp 1-11 (2019) BMC Medical Research Methodology |
ISSN: | 1471-2288 |
DOI: | 10.1186/s12874-019-0760-6 |
Popis: | Background Cluster randomised trials with unequal sized clusters often have lower precision than with clusters of equal size. To allow for this, sample sizes are inflated by a modified version of the design effect for clustering. These inflation factors are valid under the assumption that randomisation is stratified by cluster size. We investigate the impact of unequal cluster size when that constraint is relaxed, with particular focus on the stepped-wedge cluster randomised trial, where this is more difficult to achieve. Methods Assuming a multi-level mixed effect model with exchangeable correlation structure for a cross-sectional design, we use simulation methods to compare the precision for a trial with clusters of unequal size to a trial with clusters of equal size (relative efficiency). For a range of scenarios we illustrate the impact of various design features (the cluster-mean correlation – a function of the intracluster correlation and the cluster size, the number of clusters, number of randomisation sequences) on the average and distribution of the relative efficiency. Results Simulations confirm that the average reduction in precision, due to varying cluster sizes, is smaller in a stepped-wedge trial compared to the parallel trial. However, the variance of the distribution of the relative efficiency is large; and is larger under the stepped-wedge design compared to the parallel design. This can result in large variations in actual power, depending on the allocation of clusters to sequences. Designs with larger variations in cluster sizes, smaller number of clusters and studies with smaller cluster-mean correlations (smaller cluster sizes or smaller intra-cluster correlation) are particularly at risk. Conclusion The actual realised power in a stepped-wedge trial might be substantially higher or lower than that estimated. This is particularly important when there are a small number of clusters or the variability in cluster sizes is large. Constraining the randomisation on cluster size, where feasible, might mitigate this effect. Electronic supplementary material The online version of this article (10.1186/s12874-019-0760-6) contains supplementary material, which is available to authorized users. |
Databáze: | OpenAIRE |
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