Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Pragmatiskais ABAB dizains× | Pārtraukto laika sēriju (ITS) analīze× | |
|---|---|---|
| Nozare≠ | Eksperimentu plānošana | Cēloņsakarību secināšana |
| Saime≠ | Process / pipeline | Regression model |
| Izcelsmes gads≠ | 1968 (classic ABAB); pragmatic adaptations formalised 1990s–2000s | 2002 |
| Autors≠ | 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) |
| Tips≠ | Single-case experimental design | Quasi-experimental segmented regression |
| Pirmavots≠ | 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. DOI ↗ |
| Citi nosaukumi≠ | 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 |
| Saistītās≠ | 2 | 5 |
| Kopsavilkums≠ | 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. |
| ScholarGateDatu kopa ↗ |
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