ArticleInternational journal of epidemiology2023
Estimands in cluster-randomized trials: choosing analyses that answer the right question.
Article in International journal of epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 1 of them a synthesis that pooled it.
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Who cites it
73 citing papers in PubMed, 1 synthesis or guideline pooled it.
- We should do better in accounting for multiple births in neonatal randomised trials: a methodological systematic review.Archives of disease in childhood. Fetal and neonatal edition · 2025Pooled it
- Primary Care-Based Digital Health-Enabled Stroke Management Intervention: Long-Term Follow-Up of a Cluster Randomized Clinical Trial.JAMA network open · 2024Trial
- Trial
- Household Air Pollution and Child Lung Function: The Ghana Randomized Air Pollution and Health Study.American journal of respiratory and critical care medicine · 2024Trial
- Peer Comparison or Guideline-Based Feedback and Postsurgery Opioid Prescriptions: A Randomized Clinical Trial.JAMA health forum · 2024Trial
- Trial
- Informative cluster size in cluster-randomised trials: A case study from the TRIGGER trial.Clinical trials (London, England) · 2023Trial
- Effect of community health worker home visits on antenatal care and institutional delivery: an analysis of secondary outcomes from a cluster randomised trial in Mali.BMJ global health · 2023Trial
- The association between oral health clusters and oral health-related quality of life: A population‑based study of 5‑yr‑old children.European journal of oral sciences · 2026Article
- What is estimated in cluster randomized crossover trials with informative sizes? A survey of estimands and common estimators.Statistical methods in medical research · 2026Article
- A validity-guided workflow for robust large language model research in psychology.Behavior research methods · 2026Article
- Repeated sampling of different individuals within the same clusters to improve precision of longitudinal estimators: the DISC design.International journal of epidemiology · 2026Article
- Doubly Robust Estimators of the Restricted Mean Time in Favor Estimands in Individual- and Cluster-Randomized Trials.Statistics in medicine · 2026Article
- Principal stratification with U-statistics under principal ignorability.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2026Article
- CRT-Estimands Framework: consensus based extension of the ICH E9(R1) addendum for cluster randomised trials.BMJ (Clinical research ed.) · 2026Article
- Model-robust standardization in stepped wedge cluster randomized trials.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2026Article
- Article
- Use of estimands in cluster randomised trials: A review.Clinical trials (London, England) · 2026Review
- Design of Bayesian Clinical Trials With Clustered Data.Statistics in medicine · 2026Article
- Estimands and Doubly Robust Estimation for Cluster-Randomized Trials With Survival Outcomes.Statistics in medicine · 2026Article
13 more citing papers are in PubMed but not listed here.
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Authors and funding
4 authors.
Funding
Abstract
backgroundCluster-randomized trials (CRTs) involve randomizing groups of individuals (e.g. hospitals, schools or villages) to different interventions. Various approaches exist for analysing CRTs but there has been little discussion around the treatment effects (estimands) targeted by each.
methodsWe describe the different estimands that can be addressed through CRTs and demonstrate how choices between different analytic approaches can impact the interpretation of results by fundamentally changing the question being asked, or, equivalently, the target estimand.
resultsCRTs can address either the participant-average treatment effect (the average treatment effect across participants) or the cluster-average treatment effect (the average treatment effect across clusters). These two estimands can differ when participant outcomes or the treatment effect depends on the cluster size (referred to as 'informative cluster size'), which can occur for reasons such as differences in staffing levels or types of participants between small and large clusters. Furthermore, common estimators, such as mixed-effects models or generalized estimating equations with an exchangeable working correlation structure, can produce biased estimates for both the participant-average and cluster-average treatment effects when cluster size is informative. We describe alternative estimators (independence estimating equations and cluster-level analyses) that are unbiased for CRTs even when informative cluster size is present.
conclusionWe conclude that careful specification of the estimand at the outset can ensure that the study question being addressed is clear and relevant, and, in turn, that the selected estimator provides an unbiased estimate of the desired quantity.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.