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Some methodological issues in the design and analysis of cluster randomised trials
  1. Mohammad A Mansournia1,2,
  2. Douglas G Altman3
  1. 1 Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  2. 2 Sports Medicine Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
  3. 3 Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Centre for Statistics in Medicine, University of Oxford, Oxford, UK
  1. Correspondence to Professor Mohammad A Mansournia, Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran; mansournia_ma{at}yahoo.com

https://doi.org/10.1136/bjsports-2018-099628

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    Randomised trials are widely used for assessing the effect of interventions on outcomes, because on average randomisation balances covariates between treatment groups, even if those covariates are unobserved.1 2 In some situations, it is more convenient to assign treatments at random to clusters (eg, clubs, schools, teams and so on) into which individuals fall naturally. This design, which minimises the risk of contamination that would occur if individuals from the same cluster were randomised to different treatment groups, is a cluster randomised controlled trial.3 Several recent BJSM papers have reported cluster randomised trials.4–6 Among these, two studies assessed the effect of movement control exercise programmes on musculoskeletal injury and concussion risk in schoolboy and adult rugby players4 5 and a third assessed the effect of an exercise programme on the prevalence of shoulder problems in elite handball players.6 Here we review some important methodological aspects of cluster randomised controlled trials in the context of these studies. Some of these issues also affect individual randomised trials.

    Design effect

    The most important methodological aspect of cluster randomised trial is that the effective sample size is less than the number of recruited individuals because the responses of individuals within the same cluster are likely to be positively correlated. As a result, the variance of the effect estimate in cluster randomised trials will be inflated compared with an individual randomised trial with the same sample size. This variance inflation factor, sometimes known as the design effect, increases with both intracluster correlation coefficient (ie, the proportion of the total variance of the effect estimate which can be explained by the variation between clusters) and average cluster size.

    Although the value of intracluster correlation coefficient in cluster randomised trial tends to be small (typically <0.1), the resulting design effect can be quite substantial if the clusters are large. The …

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    Footnotes

    • Competing interests None declared.

    • Provenance and peer review Commissioned; internally peer reviewed.