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.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- 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
- Hayes, R. J., & Moulton, L. H. (2017). Cluster Randomised Trials (2nd ed.). CRC Press. · ISBN 9781498728874
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.