Methoden vergelijken

	Factoriële single-subject experimentele opzet	Crossover Single-Subject Experimenteel Ontwerp
Vakgebied	Experimenteel ontwerp	Experimenteel ontwerp
Familie	Process / pipeline	Process / pipeline
Jaar van ontstaan	1970s–1980s	1970s–1980s (single-case crossover formalized in behavioral research context)
Grondlegger	Applied behavior analysis tradition; systematized in Barlow & Hersen (1984) and Kazdin (1982)	Developed within the single-case research tradition; crossover application formalized by Barlow and Hersen and expanded by Kazdin
Type	Experimental single-subject design with multiple independent variables	Experimental single-subject design
Oorspronkelijke bron	Kazdin, A. E. (2011). Single-Case Research Designs: Methods for Clinical and Applied Settings (2nd ed.). Oxford University Press. ISBN: 978-0195341881	Kazdin, A. E. (2011). Single-Case Research Designs: Methods for Clinical and Applied Settings (2nd ed.). Oxford University Press. ISBN: 978-0195341881
Aliassen	factorial SCED, factorial single-case design, factorial N-of-1 design, factorial within-subject experimental design	crossover SSED, alternating-treatments crossover design, single-case crossover design, N-of-1 crossover design
Verwant	6	4
Samenvatting	A factorial single-subject experimental design applies the logic of factorial experiments — manipulating two or more independent variables simultaneously to study main effects and interactions — within a single-subject (N=1 or small N) repeated-measures framework. Instead of comparing groups, the same individual serves as their own control across systematically varied conditions, enabling fine-grained analysis of how multiple treatment components combine to influence behavior or clinical outcomes.	The crossover single-subject experimental design (crossover SSED) applies two or more treatment conditions sequentially to the same individual, with a washout or return-to-baseline period between conditions. Because each participant serves as their own control, between-subject variability is eliminated, enabling precise causal inference about treatment effects even with very small samples — often a single participant. This design is widely used in applied behavior analysis, special education, rehabilitation, and clinical psychology.