Сравнение на методи
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| Адаптивен AB дизайн× | Адаптивен експеримент× | |
|---|---|---|
| Област | Планиране на експеримента | Планиране на експеримента |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1968 (AB foundation); 2000s (adaptive extensions) | 1940s–1970s (sequential foundations); formalised in clinical and behavioural research by 1980s–2000s |
| Създател≠ | Baer, Wolf & Risley (AB foundation); Kratochwill & Levin (adaptive single-case extensions) | Abraham Wald (sequential analysis foundation); expanded by Robbins, Armitage, and others |
| Тип≠ | Single-subject experimental design with adaptive phase-change rules | Experimental research design |
| Основополагащ източник≠ | 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 |
| Други названия | adaptive single-case AB design, data-driven AB design, adaptive baseline-intervention design, adaptive AB phase design | adaptive design, response-adaptive randomization, adaptive trial, adaptive randomization |
| Свързани≠ | 6 | 5 |
| Резюме≠ | The adaptive AB design is a single-subject experimental design that retains the two-phase baseline-then-intervention structure of the classic AB design but replaces fixed session-count rules with pre-specified data-driven criteria — such as stability thresholds or trend benchmarks — that determine when to transition between phases. This adaptive logic allows the phase boundary to move in response to the individual participant's actual performance trajectory rather than a predetermined schedule. | 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. |
| ScholarGateНабор от данни ↗ |
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