ArticleStatistical methods in medical research2017
Sample size determinations for group-based randomized clinical trials with different levels of data hierarchy between experimental and control arms.
Article in Statistical methods in medical research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Optimal allocation to treatments in a sequential multiple assignment randomized trial.Statistical methods in medical research · 2021Trial
- Efficient design of partially nested randomized trials: A maximin approach.Statistical methods in medical research · 2026Article
- Designing individually randomized group treatment trials with repeated outcome measurements using generalized estimating equations.Statistics in medicine · 2024Article
- Partially clustered designs for clinical trials: Unifying existing designs using consistent terminology.Clinical trials (London, England) · 2023Review
- Optimal allocations for two treatment comparisons within the proportional odds cumulative logits model.PloS one · 2021Article
- Improving the Youth HIV Prevention and Care Cascades: Innovative Designs in the Adolescent Trials Network for HIV/AIDS Interventions.AIDS patient care and STDs · 2019Review
- Cost-efficient designs for three-arm trials with treatment delivered by health professionals: Sample sizes for a combination of nested and crossed designs.Clinical trials (London, England) · 2018Article
- Review of Recent Methodological Developments in Group-Randomized Trials: Part 1-Design.American journal of public health · 2017Review
- Multilevel Interventions Targeting Obesity: Research Recommendations for Vulnerable Populations.American journal of preventive medicine · 2017Article
- Recommendations for the analysis of individually randomised controlled trials with clustering in one arm - a case of continuous outcomes.BMC medical research methodology · 2016Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
We derived sample size formulae for detecting main effects in group-based randomized clinical trials with different levels of data hierarchy between experimental and control arms. Such designs are necessary when experimental interventions need to be administered to groups of subjects whereas control conditions need to be administered to individual subjects. This type of trial, often referred to as a partially nested or partially clustered design, has been implemented for management of chronic diseases such as diabetes and is beginning to emerge more commonly in wider clinical settings. Depending on the research setting, the level of hierarchy of data structure for the experimental arm can be three or two, whereas that for the control arm is two or one. Such different levels of data hierarchy assume correlation structures of outcomes that are different between arms, regardless of whether research settings require two or three level data structure for the experimental arm. Therefore, the different correlations should be taken into account for statistical modeling and for sample size determinations. To this end, we considered mixed-effects linear models with different correlation structures between experimental and control arms to theoretically derive and empirically validate the sample size formulae with simulation studies.
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Registered trials
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