เปรียบเทียบวิธี
ดูวิธีที่เลือกเทียบกันแบบเคียงข้าง แถวที่ต่างกันจะถูกเน้นไว้
| การทดลองแบบปรับตัว× | การทดลองแบบหลายแขน× | |
|---|---|---|
| สาขาวิชา | การออกแบบการทดลอง | การออกแบบการทดลอง |
| ตระกูล | Process / pipeline | Process / pipeline |
| ปีกำเนิด≠ | 1940s–1970s (sequential foundations); formalised in clinical and behavioural research by 1980s–2000s | 1990s–2000s (clinical formalization); multi-arm concept implicit in ANOVA-era factorial designs |
| ผู้ริเริ่ม≠ | Abraham Wald (sequential analysis foundation); expanded by Robbins, Armitage, and others | Developed within clinical trials methodology; formalized by Parmar, Royston and colleagues (UK MRC CTU, early 2000s) |
| ประเภท≠ | Experimental research design | Experimental design |
| แหล่งต้นตำรับ≠ | Chow, S. C., & Chang, M. (2008). Adaptive Design Methods in Clinical Trials. Chapman and Hall/CRC. ISBN: 978-1584886761 | Royston, P., Parmar, M. K. B., & Qian, W. (2003). Novel designs for multi-arm clinical trials with survival outcomes with an application in ovarian cancer. Statistics in Medicine, 22(14), 2239–2256. DOI ↗ |
| ชื่อเรียกอื่น | adaptive design, response-adaptive randomization, adaptive trial, adaptive randomization | multi-arm trial, multiple-arm experiment, multi-group experiment, many-arm design |
| ที่เกี่ยวข้อง | 5 | 5 |
| สรุป≠ | 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. | A multi-arm experiment simultaneously compares three or more treatment or intervention conditions — each called an arm — against a shared control or against one another. By testing multiple alternatives in a single study, it yields more information per participant than running separate two-group experiments sequentially, while controlling the overall Type I error rate through pre-specified comparison strategies. |
| ScholarGateชุดข้อมูล ↗ |
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