ArticleBMC medical research methodology2022
Cluster randomised trials with a binary outcome and a small number of clusters: comparison of individual and cluster level analysis method.
Article in BMC medical research methodology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Analysing cluster randomised controlled trials using GLMM, GEE1, GEE2, and QIF: results from four case studies.BMC medical research methodology · 2023Pooled it
- Effects of traditional culture picture book intervention on emotional regulation ability and neuropsychology of preschool children.Frontiers in public health · 2026Trial
- Digital Detection of Dementia in Primary Care: A Randomized Clinical Trial.JAMA network open · 2025Trial
- The Impact of a Household Intervention on ART Adherence and Household HIV Competency for People Living with HIV: Results from a Cluster-Randomised Controlled Trial in Cape Town, South Africa.AIDS and behavior · 2026Article
- Determining the Impact of a Physiotherapist-Led Primary Care Model for Hip and Knee Pain: Protocol and Analysis Plan for a Cluster Randomized Controlled Trial With Process Evaluation.JMIR research protocols · 2026Article
- Determining the Impact of a Physiotherapist-Led Primary Care Model for Low Back Pain: Protocol and Analysis Plan for a Cluster Randomized Controlled Trial and Embedded Process Evaluation.JMIR research protocols · 2026Article
- Article
- Enhancing District Health Center membership among older adults through intergenerational home-based and AI-generated digital interventions: protocol for a pilot cluster randomized controlled trial.Frontiers in public health · 2026Article
- Article
- Association of distance to diagnosis and area-based social measures with stage at diagnosis among Iowans with HPV-related cancers.Cancer causes & control : CCC · 2025Article
- Weighting methods for truncation by death in cluster-randomized trials.Statistical methods in medical research · 2025Article
- Power and Sample Size Calculations for Cluster Randomized Hybrid Type 2 Effectiveness-Implementation Studies.Statistics in medicine · 2025Article
- Design of field trials for the evaluation of transmissible vaccines in animal populations.PLoS computational biology · 2025Article
- Article
- Article
- A cluster randomized trial assessing the effect of a digital health algorithm on quality of care in Tanzania (DYNAMIC study).PLOS digital health · 2024Article
- Demystifying estimands in cluster-randomised trials.Statistical methods in medical research · 2024Article
- Integrating SARS-CoV-2 rapid antigen testing in maternal, neonatal and child health, HIV and tuberculosis services in Cameroon and Kenya: a cluster randomised trial of two testing models.BMJ public health · 2024Article
- Evaluating tests for cluster-randomized trials with few clusters under generalized linear mixed models with covariate adjustment: A simulation study.Statistics in medicine · 2024Article
- Cluster randomized controlled trial analysis at the cluster level: The clan command.The Stata journal · 2023Article
Corrections and comments
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4 authors.
Funding
Abstract
backgroundCluster randomised trials (CRTs) are often designed with a small number of clusters, but it is not clear which analysis methods are optimal when the outcome is binary. This simulation study aimed to determine (i) whether cluster-level analysis (CL), generalised linear mixed models (GLMM), and generalised estimating equations with sandwich variance (GEE) approaches maintain acceptable type-one error including the impact of non-normality of cluster effects and low prevalence, and if so (ii) which methods have the greatest power. We simulated CRTs with 8-30 clusters, altering the cluster-size, outcome prevalence, intracluster correlation coefficient, and cluster effect distribution. We analysed each dataset with weighted and unweighted CL; GLMM with adaptive quadrature and restricted pseudolikelihood; GEE with Kauermann-and-Carroll and Fay-and-Graubard sandwich variance using independent and exchangeable working correlation matrices. P-values were from a t-distribution with degrees of freedom (DoF) as clusters minus cluster-level parameters; GLMM pseudolikelihood also used Satterthwaite and Kenward-Roger DoF.
resultsUnweighted CL, GLMM pseudolikelihood, and Fay-and-Graubard GEE with independent or exchangeable working correlation matrix controlled type-one error in > 97% scenarios with clusters minus parameters DoF. Cluster-effect distribution and prevalence of outcome did not usually affect analysis method performance. GEE had the least power. With 20-30 clusters, GLMM had greater power than CL with varying cluster-size but similar power otherwise; with fewer clusters, GLMM had lower power with common cluster-size, similar power with medium variation, and greater power with large variation in cluster-size.
conclusionWe recommend that CRTs with ≤ 30 clusters and a binary outcome use an unweighted CL or restricted pseudolikelihood GLMM both with DoF clusters minus cluster-level parameters.
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