The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Sequential Treatment Assignment with Balancing for Prognostic Factors in the Controlled Clinical Trial
Abstract
In controlled clinical trials there are usually several prognostic factors known or thought to influence the patient's ability to respond to treatment. Therefore, the method of sequential treatment assignment needs to be designed so that treatment balance is simultaneously achieved across all such patients factor. Traditional methods of restricted randomization such as "permuted blocks within strata" prove inadequate once the number of strata, or combinations of factor levels, approaches the sample size. A new general procedure for treatment assignment is described which concentrates on minimizing imbalance in the distributions of treatment numbers within the levels of each individual prognostic factor. The improved treatment balance obtained by this approach is explored using simulation for a simple model of a clinical trial. Further discussion centers on the selection, predictability and practicability of such a procedure.
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“On the other hand, although balance in sample size may be achieved with this method, groups may be generated that are rarely comparable in terms of certain covariates, which could introduce bias in the statistical analysis and reduce the power of the study. Consequently, sample size and covariates should had been balanced in this clinical research [70].”
From Early Occupational Therapy Intervention post-stroke (EOTIPS): A randomized controlled trial (2024) · cites this paper as [70]
In the citing paper
“were randomly allocated to receive empagliflozin (10 mg once daily) or matching placebo using minimized randomization with a 10% stochastic element.17”
From Empagliflozin in Patients with Chronic Kidney Disease (2023) · cites this paper as [17]
In the citing paper
“The minimization randomization method, which is a deterministic scheme for allocating treatment with the goal of balancing prognostic factors, was applied to ensure equal participant numbers in each treatment group over multiple strata (i.e., equal number of participants in each arm within a fixed block size of four).(41)”
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Cites
Forcing a sequential experiment to be balanced
EFRON, B. (1971) · Biometrika · doi:10.1093/biomet/58.3.403 · Cited by 873
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Metadata
- Authors
- Pocock, S. J., & Simon, R.
- Venue
- Biometrics
- Publisher
- JSTOR
- Published
- 1975-03
- Volume
- 31
- Issue
- 1
- Pages
- 103
- ISSN
- 0006-341X (ISSN-L)
- OpenAlex
- W2000366267
- Cited by
- 2,350
- References
- 1
- Citations by year
- 2026: 67 · 2025: 90 · 2024: 84 · 2023: 93 · 2022: 84 · 2021: 94 · 2020: 100 · 2019: 93 · 2018: 95 · 2017: 102 · 2016: 100 · 2015: 82 · 2014: 105 · 2013: 88 · 2012: 119
- FWCI
- 9.36
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Biometrics (publishedVersion)
- PubMed (publishedVersion)
- 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
- prognostic factors, restricted randomization, stratified randomization, clinical trials
- MeSH terms
- Carmustine, Clinical Trials as Topic, Cyclophosphamide, Evaluation Studies as Topic, Humans, Lymphoma, Models, Theoretical, Prednisone, Prognosis, Statistics as Topic, Vincristine
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