Kahan, Brennan C;
Blette, Bryan S;
Harhay, Michael O;
Halpern, Scott D;
Jairath, Vipul;
Copas, Andrew;
Li, Fan;
(2024)
Demystifying estimands in cluster-randomised trials.
Statistical Methods in Medical Research
10.1177/09622802241254197.
(In press).
Preview |
Text
kahan-et-al-2024-demystifying-estimands-in-cluster-randomised-trials.pdf - Published Version Download (1MB) | Preview |
Abstract
Estimands can help clarify the interpretation of treatment effects and ensure that estimators are aligned with the study's objectives. Cluster-randomised trials require additional attributes to be defined within the estimand compared to individually randomised trials, including whether treatment effects are marginal or cluster-specific, and whether they are participant- or cluster-average. In this paper, we provide formal definitions of estimands encompassing both these attributes using potential outcomes notation and describe differences between them. We then provide an overview of estimators for each estimand, describe their assumptions, and show consistency (i.e. asymptotically unbiased estimation) for a series of analyses based on cluster-level summaries. Then, through a re-analysis of a published cluster-randomised trial, we demonstrate that the choice of both estimand and estimator can affect interpretation. For instance, the estimated odds ratio ranged from 1.38 (p = 0.17) to 1.83 (p = 0.03) depending on the target estimand, and for some estimands, the choice of estimator affected the conclusions by leading to smaller treatment effect estimates. We conclude that careful specification of the estimand, along with an appropriate choice of estimator, is essential to ensuring that cluster-randomised trials address the right question.
| Type: | Article |
|---|---|
| Title: | Demystifying estimands in cluster-randomised trials |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1177/09622802241254197 |
| Publisher version: | http://dx.doi.org/10.1177/09622802241254197 |
| Language: | English |
| Additional information: | © The Author(s) 2024. Creative Commons License (CC BY 4.0) This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
| Keywords: | Science & Technology, Life Sciences & Biomedicine, Physical Sciences, Health Care Sciences & Services, Mathematical & Computational Biology, Medical Informatics, Statistics & Probability, Mathematics, Estimand, cluster-randomised trial, independence estimating equations, analysis of cluster-level summaries, participant-average, cluster-average, marginal, cluster-specific, RECENT METHODOLOGICAL DEVELOPMENTS, SIZE |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute for Global Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology > MRC Clinical Trials Unit at UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute for Global Health > Infection and Population Health |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10193812 |
Archive Staff Only
 |
View Item |
