Comparer des méthodes

	Plan à bases multiples en double aveugle	Essai contrôlé randomisé croisé
Domaine	Plans d'expériences	Plans d'expériences
Famille	Process / pipeline	Process / pipeline
Année d'origine	1968 (multiple baseline); double-blind extension applied from 1980s onward in clinical behavioral research	1960s (Grizzle 1965 for statistical foundations); widely used in clinical research since the 1970s
Auteur d'origine	Multiple baseline: Baer, Wolf & Risley (1968); double-blind procedural extension adapted from clinical trial methodology	Early formalized by statisticians including Bradford Hill and colleagues in clinical trials; theoretical framework developed by Grizzle (1965) and later Senn (2002)
Type	Single-subject experimental design with blinded outcome assessment	Experimental within-subject design
Source fondatrice	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
Alias	DB-MBD, blinded multiple baseline design, masked multiple baseline design, double-blind MBD	crossover RCT, crossover trial, within-subject RCT, AB/BA crossover design
Apparentées	5	5
Résumé	The double-blind multiple baseline design is a single-subject experimental design in which an intervention is introduced sequentially across two or more independent baselines — behaviors, individuals, or settings — while outcome assessors (and ideally participants) remain unaware of which baseline is currently in the intervention phase. The double-blind procedural overlay reduces measurement bias and demand characteristics, strengthening causal inference beyond what a standard multiple baseline design offers.	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.