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Cited by 298Statistical Methods in Clinical TrialsHealth Policy Implementation ScienceMeta-analysis and systematic reviews

The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.

Sample Size Calculations for Cluster Randomised Trials

Campbell, Marion, Grimshaw, Jeremy, Steen, Nick, Changing Professional Practice in Europe Group (EU BIOMED II Concerted Action)·2000·Journal of Health Services Research & Policy
DOI 10.1177/135581960000500105
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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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Research works printed but not linked: 2

  1. Morgan M, 1978, Quality Review Bulletin, 4, 33
  2. Donner A., 1998, Applied Statistics, 47, 95

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Metadata

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)
ORCID
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
DOI
10.1177/135581960000500105
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
Licence
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
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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