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| Single-blind Multi-arm Experiment× | Adaptivt eksperiment× | |
|---|---|---|
| Fagområde | Forsøgsdesign | Forsøgsdesign |
| Familie | Process / pipeline | Process / pipeline |
| Oprindelsesår≠ | Mid-to-late 20th century | 1940s–1970s (sequential foundations); formalised in clinical and behavioural research by 1980s–2000s |
| Ophavsperson≠ | Developed within the clinical trials tradition; formalized by Friedman, Furberg, and DeMets and others in the 20th century | Abraham Wald (sequential analysis foundation); expanded by Robbins, Armitage, and others |
| Type≠ | Controlled experimental design | Experimental research design |
| Oprindelig kilde≠ | Friedman, L. M., Furberg, C. D., & DeMets, D. L. (2010). Fundamentals of Clinical Trials (4th ed.). Springer. ISBN: 978-1441915849 | Chow, S. C., & Chang, M. (2008). Adaptive Design Methods in Clinical Trials. Chapman and Hall/CRC. ISBN: 978-1584886761 |
| Aliasser | single-masked multi-arm trial, single-blind multi-group experiment, unidirectional blinding multi-arm design, SB-MAT | adaptive design, response-adaptive randomization, adaptive trial, adaptive randomization |
| Relaterede | 5 | 5 |
| Resumé≠ | A single-blind multi-arm experiment is a controlled experimental design that simultaneously compares three or more treatment conditions while blinding participants — but not investigators — to their group assignment. This configuration reduces response bias driven by participants' expectations, preserves operational feasibility when full blinding is impractical, and allows direct pairwise and omnibus comparisons across multiple arms within a single study. | 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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