방법 비교

	Crossover A/B Test	차단된 A/B 테스트
분야	실험설계	실험설계
계열	Process / pipeline	Process / pipeline
기원 연도	1949 (crossover design); 2000s (online A/B application)	1926 (blocking principle); 2000s–2010s (online A/B testing application)
창시자	Crossover design: E. J. Williams (1949); A/B testing framework: Ronald Fisher (experimental roots); modern online application widely attributed to Google and Microsoft experimentation teams	R. A. Fisher (blocking principle); adapted to online A/B testing by industry practitioners
유형	Within-subject controlled experiment	Randomized controlled experiment with variance reduction
원전	Jones, B., & Kenward, M. G. (2014). Design and Analysis of Cross-Over Trials (3rd ed.). Chapman and Hall/CRC. ISBN: 9781439861424	Fisher, R. A. (1926). The arrangement of field experiments. Journal of the Ministry of Agriculture of Great Britain, 33, 503–513.
별칭	within-subject A/B test, crossover split test, repeated-measures A/B test, AB crossover experiment	block-randomized A/B test, stratified A/B test, blocked split test, block-design A/B experiment
관련	6	4
요약	A crossover A/B test is an experimental design in which the same participants or units are exposed to both treatment A and treatment B in sequence, with each serving as their own control. By eliminating between-subject variability, the design achieves higher statistical power than a standard parallel A/B test at the same sample size, but it requires careful handling of carryover effects and time-period confounds.	A blocked A/B test is an experimental design that partitions units (users, subjects, or clusters) into homogeneous blocks before randomly assigning them to treatment A or treatment B within each block. Blocking reduces within-experiment noise by ensuring that known sources of variation — such as device type, geography, or user tenure — are balanced across conditions, yielding more precise estimates of the treatment effect than a simple unblocked A/B test.