Sample Size Calculations for Cluster Randomised Trials
Abstract
OBJECTIVES: Cluster randomised trials, in which groups of individuals are randomised, are increasingly being used in the health field. Adopting a clustered approach has implications for the design of such trials, and sample size calculations need to be inflated to accommodate for the clustering effect. Reliable estimates of intracluster correlation coefficients (ICCs) are required for robust sample size calculations to be made; however, little empirical evidence is available on their likely size, and on factors which influence their magnitude. The aim of this study was to generate empirical estimates of ICCs and to explore factors which may affect their magnitude. METHODS: Empirical estimates of ICCs were calculated for both process variables and patient outcomes from a number of datasets of primary and secondary care implementation studies. RESULTS: Estimates of ICCs varied according to setting and type of outcome. Estimates of ICCs for process variables were higher than those for patient outcomes, and estimates derived from secondary care were higher than those from primary care. ICCs for process variables in primary care were of the order of 0.05-0.15, whilst those in secondary care were of the order of 0.3. Estimates for patient outcomes in primary care were generally lower than 0.05. CONCLUSIONS: Adopting cluster randomisation has implications for the design, size and analysis of clinical trials. This study gives an insight into the potential size of ICCs in primary and secondary care, and provides a practical guide to researchers to aid the planning of future studies in this area.
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Based on an average cluster size of 13 evaluable participants and a therapist intraclass correlation coefficient of 0.05, 364 evaluable patients at 3 months would provide 92% power to detect the difference with a two-sample test and a significance level of 5%.
“Based on an average cluster size of 13 evaluable participants (those completing 3 months follow-up), and a therapist (health professional delivering the intervention) intraclass correlation coefficient of 0.05(ref. 30) in the intervention arm, a total of 364 evaluable patients at 3 months would provide 92% power to detect such a difference with a two-sample test and a significance level of 5%.31”
From A brief intervention for weight control based on habit-formation theory delivered through primary care: results from a randomised controlled trial (2017) · cites this paper as [30]
Studies that added CBT or pharmacotherapy to gradual dose reduction have reported inconsistent results.
“The results of studies on such strategies have been inconsistent.”
From Comparative efficacy of two interventions to discontinue long-term benzodiazepine use: cluster randomised controlled trial in primary care (2014) · cites this paper as [23]
One trial found adding CBT of limited benefit, while other trials found it helped discontinuation.
“adding CBT was of limited value in one trial, 22 but facilitated discontinuation in other trials. 23,24”
From Comparative efficacy of two interventions to discontinue long-term benzodiazepine use: cluster randomised controlled trial in primary care (2014) · cites this paper as [23]
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Self-citation
- Authors
- Campbell, M., Grimshaw, J., Steen, N., & Changing Professional Practice in Europe Group (EU BIOMED II Concerted Action)
- Affiliations
- University of Aberdeen (GB)
- Newcastle University (GB)
- Venue
- Journal of Health Services Research & Policy
- Publisher
- SAGE Publications
- Published
- 2000-01
- Volume
- 5
- Issue
- 1
- Pages
- 12-16
- ISSN
- 1355-8196 (ISSN-L)
- 1758-1060
- OpenAlex
- W170006779
- Cited by
- 298
- References
- 18
- Citations by year
- 2026: 5 · 2025: 5 · 2024: 5 · 2023: 8 · 2022: 7 · 2021: 14 · 2020: 13 · 2019: 14 · 2018: 9 · 2017: 11 · 2016: 17 · 2015: 14 · 2014: 23 · 2013: 11 · 2012: 23
- FWCI
- 12.89
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Health Services Research & Policy (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Medical Research Council
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- sample size determination, intra-cluster correlation, cluster effect, primary care, secondary care, implementation research, process parameters, patient outcomes, trial design
- MeSH terms
- Europe, Health Services Research, Humans, Outcome and Process Assessment, Health Care, Sampling Studies, Cluster Analysis, Randomized Controlled Trials as Topic
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