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Allocation techniques for balance at baseline in cluster randomized trials: a methodological review

Overview of attention for article published in Trials, August 2012
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Title
Allocation techniques for balance at baseline in cluster randomized trials: a methodological review
Published in
Trials, August 2012
DOI 10.1186/1745-6215-13-120
Pubmed ID
Authors

Noah M Ivers, Ilana J Halperin, Jan Barnsley, Jeremy M Grimshaw, Baiju R Shah, Karen Tu, Ross Upshur, Merrick Zwarenstein

Abstract

Reviews have repeatedly noted important methodological issues in the conduct and reporting of cluster randomized controlled trials (C-RCTs). These reviews usually focus on whether the intracluster correlation was explicitly considered in the design and analysis of the C-RCT. However, another important aspect requiring special attention in C-RCTs is the risk for imbalance of covariates at baseline. Imbalance of important covariates at baseline decreases statistical power and precision of the results. Imbalance also reduces face validity and credibility of the trial results. The risk of imbalance is elevated in C-RCTs compared to trials randomizing individuals because of the difficulties in recruiting clusters and the nested nature of correlated patient-level data. A variety of restricted randomization methods have been proposed as way to minimize risk of imbalance. However, there is little guidance regarding how to best restrict randomization for any given C-RCT. The advantages and limitations of different allocation techniques, including stratification, matching, minimization, and covariate-constrained randomization are reviewed as they pertain to C-RCTs to provide investigators with guidance for choosing the best allocation technique for their trial.

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The data shown below were compiled from readership statistics for 217 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 2 <1%
Netherlands 1 <1%
Qatar 1 <1%
Australia 1 <1%
Unknown 212 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 42 19%
Student > Master 37 17%
Student > Ph. D. Student 35 16%
Professor 15 7%
Professor > Associate Professor 9 4%
Other 39 18%
Unknown 40 18%
Readers by discipline Count As %
Medicine and Dentistry 62 29%
Nursing and Health Professions 19 9%
Social Sciences 16 7%
Psychology 13 6%
Agricultural and Biological Sciences 9 4%
Other 38 18%
Unknown 60 28%