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Cluster Randomized A/B Test

A cluster randomized A/B test is an experimental design in which intact groups (clusters) — such as cities, schools, social network communities, or app user segments — are randomly assigned as whole units to either the treatment (A) or control (B) condition, rather than randomizing individual users or subjects. This approach is used when treatment effects would spill over between individuals if individual-level randomization were applied, or when the intervention must be delivered at the group level.

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Sources

  1. Ugander, J., Karrer, B., Backstrom, L., & Kleinberg, J. (2013). Graph cluster randomization: Network exposure to multiple universes. Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 329–337. DOI: 10.1145/2487575.2487695
  2. Hayes, R. J., & Moulton, L. H. (2017). Cluster Randomised Trials (2nd ed.). CRC Press. ISBN: 9781498728874

Related methods

ScholarGateCluster Randomized A/B Test (Cluster Randomized A/B Test). Retrieved 2026-06-04 from https://scholargate.app/en/experimental-design/cluster-randomized-ab-test