Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Muundo wa Adaptive ABA× | Jaribio linalobadilika× | |
|---|---|---|
| Nyanja | Muundo wa Majaribio | Muundo wa Majaribio |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1968 (ABA foundation); adaptive extensions formalized ~2010–2020 | 1940s–1970s (sequential foundations); formalised in clinical and behavioural research by 1980s–2000s |
| Mwanzilishi≠ | Baer, Wolf & Risley (ABA baseline); adaptive decision-rule extensions developed in single-case methodology literature (Kratochwill & Levin, 2010s) | Abraham Wald (sequential analysis foundation); expanded by Robbins, Armitage, and others |
| Aina≠ | Single-subject experimental design with adaptive phase rules | Experimental research design |
| Chanzo asilia≠ | 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. DOI ↗ | Chow, S. C., & Chang, M. (2008). Adaptive Design Methods in Clinical Trials. Chapman and Hall/CRC. ISBN: 978-1584886761 |
| Majina mbadala | adaptive withdrawal design, adaptive ABA withdrawal design, data-driven ABA design, adaptive single-case ABA | adaptive design, response-adaptive randomization, adaptive trial, adaptive randomization |
| Zinazohusiana≠ | 6 | 5 |
| Muhtasari≠ | The Adaptive ABA Design is a single-subject experimental framework that follows the classic three-phase ABA withdrawal structure — baseline (A1), intervention (B), and return-to-baseline (A2) — while embedding prospective decision rules that allow researchers or clinicians to extend, shorten, or otherwise modify each phase in response to observed data patterns rather than following a fixed schedule. This adaptive layer makes the design responsive to individual participant trajectories while preserving experimental control. | An adaptive experiment is an experimental design in which pre-specified rules allow the protocol to be modified — such as reallocating participants to better-performing arms, stopping early for efficacy or futility, or changing sample size — based on accumulating interim data, while maintaining statistical validity. Adaptive designs are widely used in clinical trials, behavioural economics, and online platform testing to improve efficiency and ethics without sacrificing inferential rigour. |
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