Treatment allocation by minimisation
Open accessAbstract
In almost all controlled trials treatments are allocated by randomisation. Blocking and stratification can be used to ensure balance between groups in size and patient characteristics. But stratified randomisation using several variables is not effective in small trials. The only widely acceptable alternative approach is minimisation, a method of ensuring excellent balance between groups for several prognostic factors, even in small samples. With minimisation the treatment allocated to the next participant enrolled in the trial depends (wholly or partly) on the characteristics of those participants already enrolled. The aim is that each allocation should minimise the imbalance across multiple factors.
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Restricted randomization (minimization) was performed by the study registrar to prevent imbalance in smoking status and periodontitis stage.
“To prevent an imbalance between the two groups with respect to smoking status and periodontitis stage diagnosis, restricted randomization (minimization) was performed by the study registrar (Altman & Bland, 2005).”
From Enhanced control of periodontitis by an artificial intelligence‐enabled multimodal‐sensing toothbrush and targeted <scp>mHealth</scp> micromessages: A randomized trial (2024) · cites this paper as Altman & Bland, 2005
Participants were randomized to one of three treatment conditions using randomization by minimization on the basis of age, gender, IQ, medication-use, and parent- and teacher-rated inattention and hyperactivity/impulsivity symptoms.
“were independently allocated to one of the three treatment conditions using the process of randomization by minimization [82] on the basis of age, gender, IQ, medication-use (yes/no), and parent- and teacher-rated inattention and hyperactivity/impulsivity symptoms (using the 6-months DBDRS).”
A minimisation approach to randomisation will be taken in order to balance participant characteristics and numbers across conditions.
“Given that entire schools will be randomised, a minimisation approach to randomisation will be taken in order to balance participant characteristics and numbers across conditions [22, 23].”
From Silence is deadly: a cluster-randomised controlled trial of a mental health help-seeking intervention for young men (2017) · cites this paper as [22]
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Cites
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Statistics notes: How to randomise
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- Authors
- Altman, D. G., & Bland, J. M.
- Affiliations
- Cancer Research UK (GB)
- ORCID
- Altman, Douglas G
- Venue
- BMJ
- Publisher
- BMJ
- Published
- 2005-04-07
- Volume
- 330
- Issue
- 7495
- Pages
- 843
- ISSN
- 0007-1447 (ISSN-L)
- 0959-8138
- 1468-5833
- PMC
- PMC556084
- OpenAlex
- W2122588058
- Cited by
- 550
- References
- 4
- Citations by year
- 2026: 23 · 2025: 43 · 2024: 40 · 2023: 25 · 2022: 19 · 2021: 45 · 2020: 48 · 2019: 26 · 2018: 25 · 2017: 33 · 2016: 32 · 2015: 32 · 2014: 27 · 2013: 33 · 2012: 17
- FWCI
- 11.07
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- BMJ (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
- Keywords
- minimization, treatment allocation, blocking, prognostic factors, small trials, randomized controlled trials
- MeSH terms
- Epidemiologic Methods, Humans, Random Allocation, Randomized Controlled Trials as Topic, Sample Size
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