Methoden vergleichen

	Faktorielles ABAB-Design	ABAB-Design – Reversal-/Withdrawal-Design
Fachgebiet	Versuchsplanung	Versuchsplanung
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	1960s–1970s (integration of factorial and single-subject reversal traditions)	1960s (Sidman 1960; Baer et al. 1968)
Urheber	Derived from Sidman (1960) reversal logic and Fisher & Yates factorial principles; systematized in applied behavior analysis	Murray Sidman; Baer, Wolf & Risley (applied behavior analysis formalization)
Typ	Single-subject experimental design	Single-subject experimental design
Wegweisende Quelle	Kazdin, A. E. (2011). Single-Case Research Designs: Methods for Clinical and Applied Settings (2nd ed.). Oxford University Press. ISBN: 978-0195341881	Sidman, M. (1960). Tactics of Scientific Research: Evaluating Experimental Data in Psychology. Basic Books.
Aliasnamen	factorial reversal design, factorial withdrawal design, multi-factor ABAB design, factorial single-subject reversal	reversal design, withdrawal design, ABAB reversal, operant reversal design
Verwandt	5	4
Zusammenfassung	The factorial ABAB design embeds a factorial structure within the classical ABAB reversal framework, enabling a single participant or a small set of participants to experience multiple factor combinations across alternating baseline (A) and treatment (B) phases. By systematically withdrawing and reinstating treatment conditions that vary across two or more factors, the design allows examination of both main effects and interactions at the individual level, providing strong experimental control through within-subject replication.	The ABAB design is a single-subject experimental methodology that establishes causal control by repeatedly introducing and removing an intervention. A baseline phase (A) is followed by an intervention phase (B), then a return to baseline (A), and a second intervention phase (B), allowing the researcher to demonstrate that observed behavior changes are produced by the intervention rather than by coincidental factors.