So sánh phương pháp

	Kiểm định A/B ngẫu nhiên theo cụm	Thử nghiệm kiểm soát ngẫu nhiên theo cụm
Lĩnh vực	Thiết kế thí nghiệm	Thiết kế thí nghiệm
Họ	Process / pipeline	Process / pipeline
Năm ra đời	2010s (digital platforms); cluster RCT roots date to the 1970s–1980s	1978–1980s
Người khởi xướng	Developed from cluster randomized trial methodology; popularized in digital experimentation by researchers at Facebook, LinkedIn, and Microsoft Research (2010s)	Cornfield (1978); systematised by Donner and colleagues (1980s)
Loại	Experimental design	Experimental design
Công trình gốc	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.	Donner, A., & Klar, N. (2000). Design and Analysis of Cluster Randomization Trials in Health Research. Arnold. ISBN: 978-0340652978
Tên gọi khác	cluster A/B test, group-randomized A/B test, network A/B test, cluster-level split test	cluster RCT, group-randomized trial, community randomized trial, cluster-randomized experiment
Liên quan	6	4
Tóm tắt	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.	A cluster randomized controlled trial (cluster RCT) is an experimental design in which intact social or organisational groups — such as schools, clinics, villages, or workplaces — are randomly assigned to treatment conditions rather than individual participants. Outcomes are still measured at the individual level, but the unit of randomization is the cluster. This design is essential when an intervention is delivered to whole groups, when there is a risk of contamination between participants in the same setting, or when individual randomization is logistically or ethically impractical.