Порівняння методів

	Дизайн з перехресним множинним базовим рівнем	Перехресне рандомізоване контрольоване дослідження
Галузь	Планування експерименту	Планування експерименту
Родина	Process / pipeline	Process / pipeline
Рік появи	1968 (multiple baseline origins); crossover extension developed in behavioral and rehabilitation research from the 1980s onward	1960s (Grizzle 1965 for statistical foundations); widely used in clinical research since the 1970s
Автор методу	Derived from Baer, Wolf, and Risley (multiple baseline, 1968) and classical crossover design traditions	Early formalized by statisticians including Bradford Hill and colleagues in clinical trials; theoretical framework developed by Grizzle (1965) and later Senn (2002)
Тип	Single-case experimental design with crossover sequencing	Experimental within-subject design
Основоположне джерело	Baer, D. M., Wolf, M. M., & Risley, T. R. (1968). Some current dimensions of applied behavior analysis. Journal of Applied Behavior Analysis, 1(1), 91–97.	Senn, S. (2002). Cross-over Trials in Clinical Research (2nd ed.). Wiley. ISBN: 978-0471496533
Інші назви	CMBD, crossover MBD, multiple baseline crossover design, within-subject multiple baseline design	crossover RCT, crossover trial, within-subject RCT, AB/BA crossover design
Пов'язані	6	5
Підсумок	The crossover multiple baseline design is a single-case experimental design (SCED) that layers crossover sequencing onto a multiple baseline structure. Across two or more tiers — participants, behaviors, or settings — baselines are staggered in time; then treatments are introduced and later reversed or alternated across tiers, so each tier acts as both a treatment and a control unit. The design provides within-subject replication while controlling for time-related confounds.	A crossover randomized controlled trial (crossover RCT) is an experimental design in which each participant receives all study interventions in a randomized sequence, separated by a washout period. Because every participant serves as their own control, within-subject variability is eliminated from the treatment comparison, yielding greater statistical power per participant than a parallel-group RCT of equal size.