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| Adaptiivinen laboratorio koe× | Mukautuva koe× | |
|---|---|---|
| Tieteenala | Koesuunnittelu | Koesuunnittelu |
| Menetelmäperhe | Process / pipeline | Process / pipeline |
| Syntyvuosi≠ | 1947 (sequential analysis foundations); adaptive laboratory applications widespread from 1990s | 1940s–1970s (sequential foundations); formalised in clinical and behavioural research by 1980s–2000s |
| Kehittäjä≠ | Rooted in sequential analysis (Abraham Wald, 1947); adaptive clinical/lab designs formalized by Berry and colleagues (1990s–2000s) | Abraham Wald (sequential analysis foundation); expanded by Robbins, Armitage, and others |
| Tyyppi≠ | Adaptive experimental design | Experimental research design |
| Alkuperäislähde≠ | Berry, D. A. (2006). Bayesian clinical trials. Nature Reviews Drug Discovery, 5(1), 27–36. DOI ↗ | Chow, S. C., & Chang, M. (2008). Adaptive Design Methods in Clinical Trials. Chapman and Hall/CRC. ISBN: 978-1584886761 |
| Rinnakkaisnimet | adaptive lab experiment, sequential adaptive laboratory study, response-adaptive laboratory design, adaptive experimental laboratory design | adaptive design, response-adaptive randomization, adaptive trial, adaptive randomization |
| Liittyvät | 5 | 5 |
| Tiivistelmä≠ | An adaptive laboratory experiment is a controlled experimental design conducted in a laboratory setting where pre-specified decision rules allow modifications to the study — such as sample size, treatment allocation, or stopping criteria — based on accumulating data. Unlike fixed designs, adaptive designs incorporate planned interim analyses that permit the experiment to respond to emerging evidence while maintaining statistical validity and Type I error 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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