Randomization of Clusters Versus Randomization of Persons Within Clusters: Which Is Preferable?
Abstract
Many experiments aim at populations with persons nested within clusters. Randomization to treatment conditions can be done at the cluster level or at the person level within each cluster. The latter may result in control group contamination, and cluster randomization is therefore oftenpreferred in practice. This article models the control group contamination, calculates the required sample sizes for both levels of randomization, and gives the degree of contamination for which cluster randomization is preferable above randomization of persons within clusters. Moreover, itprovides examples of situations where one has to make a choice between both levels of randomization.
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In a comparison between a novel treatment and usual care any bias due to contamination will attenuate the true treatment effect.
“In a comparison between a novel treatment and usual care any bias due to contamination will attenuate the true treatment effect [18,26,35].”
From Cluster randomized trials of individual-level interventions were at high risk of bias (2021) · cites this paper as [26]
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References 15 · Cited by 17
- Authors
- Moerbeek, M.
- Affiliations
- Utrecht University (NL)
- Corresponding author
- Moerbeek, Mirjam
- ORCID
- Moerbeek, Mirjam
- Venue
- The American Statistician
- Publisher
- Informa UK Limited
- Published
- 2005-05
- Volume
- 59
- Issue
- 2
- Pages
- 173-179
- ISSN
- 0003-1305 (ISSN-L)
- 1537-2731
- OpenAlex
- W4229938155
- Cited by
- 17
- References
- 15
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1 · 2022: 1 · 2021: 3 · 2019: 3 · 2018: 1 · 2015: 4 · 2014: 1
- FWCI
- 0.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The American Statistician (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Keywords
- cluster randomization, sample size determination
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