Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Jaribio la mikono mingi× | Jaribio linalobadilika× | |
|---|---|---|
| Nyanja | Muundo wa Majaribio | Muundo wa Majaribio |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1990s–2000s (clinical formalization); multi-arm concept implicit in ANOVA-era factorial designs | 1940s–1970s (sequential foundations); formalised in clinical and behavioural research by 1980s–2000s |
| Mwanzilishi≠ | Developed within clinical trials methodology; formalized by Parmar, Royston and colleagues (UK MRC CTU, early 2000s) | Abraham Wald (sequential analysis foundation); expanded by Robbins, Armitage, and others |
| Aina≠ | Experimental design | Experimental research design |
| Chanzo asilia≠ | 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 ↗ | Chow, S. C., & Chang, M. (2008). Adaptive Design Methods in Clinical Trials. Chapman and Hall/CRC. ISBN: 978-1584886761 |
| Majina mbadala | multi-arm trial, multiple-arm experiment, multi-group experiment, many-arm design | adaptive design, response-adaptive randomization, adaptive trial, adaptive randomization |
| Zinazohusiana | 5 | 5 |
| Muhtasari≠ | 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. | 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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