Võrdle meetodeid

	Pragmatic ABAB Design	Katkendliku ajasarja (ITS) analüüs	Mitme baasi disain
Valdkond	Katsedisain	Põhjuslik järeldamine	Katsedisain
Perekond	Process / pipeline	Regression model	Process / pipeline
Tekkeaasta	1968 (classic ABAB); pragmatic adaptations formalised 1990s–2000s	2002	1968
Looja	Adapted from Baer, Wolf & Risley (1968); pragmatic variant developed in applied behavior analysis and clinical psychology literature	Wagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial)	Donald M. Baer, Montrose M. Wolf, Todd R. Risley
Tüüp	Single-case experimental design	Quasi-experimental segmented regression	Single-subject experimental design
Algallikas	Kazdin, A. E. (2011). Single-Case Research Designs: Methods for Clinical and Applied Settings (2nd ed.). Oxford University Press. ISBN: 978-0195341881	Bernal, J. L., Cummins, S., & Gasparrini, A. (2017). Interrupted time series regression for the evaluation of public health interventions: a tutorial. International Journal of Epidemiology, 46(1), 348-355.	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.
Rööpnimetused	pragmatic reversal design, pragmatic withdrawal design, applied ABAB design, pragmatic single-case reversal	ITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi	MBD, multiple-baseline single-case design, staggered baseline design, multiple-probe design
Seotud	2	5	4
Kokkuvõte	The pragmatic ABAB design is a single-case experimental design that adapts the classic reversal (ABAB) logic to real-world clinical and applied constraints. It alternates between a baseline phase (A) and an intervention phase (B) twice, demonstrating experimental control through repeated phase changes while allowing flexibility — such as abbreviated withdrawals or partial reversals — when full withdrawal of treatment is ethically or practically impossible.	Interrupted Time Series analysis is a quasi-experimental design that estimates the effect of a single, well-dated intervention by comparing the trajectory of an outcome before and after it occurs. Formalised as segmented regression by Wagner and colleagues (2002) and popularised as a public-health evaluation tutorial by Bernal, Cummins and Gasparrini (2017), it separates the intervention's impact into a change in level and a change in slope.	The multiple baseline design is a single-subject experimental design that demonstrates functional control by introducing an intervention at staggered time points across two or more baselines — typically across different behaviors, individuals, or settings. Because no withdrawal of treatment is required, it is especially suitable when the target behavior is irreversible or when removing an effective intervention would be unethical.