How should a cluster randomized trial be analyzed?

Laurent Billot; Andrew Copas; Clemence Leyrat; Andrew Forbes; Elizabeth L Turner

doi:10.1016/j.jeph.2024.202196

How should a cluster randomized trial be analyzed?

J Epidemiol Popul Health. 2024 Feb;72(1):202196. doi: 10.1016/j.jeph.2024.202196. Epub 2024 Feb 10.

Authors

Laurent Billot¹, Andrew Copas², Clemence Leyrat³, Andrew Forbes⁴, Elizabeth L Turner⁵

Affiliations

¹ The George Institute for Global Health, University of New South Wales, Sydney, Australia. Electronic address: lbillot@georgeinstitute.org.
² MRC Clinical Trials Unit at University College London, London, UK.
³ Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK.
⁴ School of Public Health and Preventive Medicine, Monash University, Victoria, Australia.
⁵ Department of Biostatistics and Bioinformatics and Duke Global Health Institute, Duke University, Durham, NC, USA.

Abstract

In cluster randomized trials, individuals from the same cluster tend to have more similar outcomes than individuals from different clusters. This correlation must be taken into account in the analysis of every cluster trial to avoid incorrect inferences. In this paper, we describe the principles guiding the analysis of cluster trials including how to correctly account for intra-cluster correlations as well as how to analyze more advanced designs such as stepped-wedge and cluster cross-over trials. We then describe how to handle specific issues such as small sample sizes and missing data.

Keywords: Analysis; Cluster crossover trials; Cluster randomized trials; Stepped-wedge trials.

MeSH terms

Cluster Analysis
Cross-Over Studies
Humans
Randomized Controlled Trials as Topic*
Research Design*
Sample Size

Abstract

MeSH terms

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