Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Jaribio Lililobadilika kwa Kubahatisha kwa Ngeli× | Jaribio linalobadilika× | |
|---|---|---|
| Nyanja | Muundo wa Majaribio | Muundo wa Majaribio |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 2000s–2010s | 1940s–1970s (sequential foundations); formalised in clinical and behavioural research by 1980s–2000s |
| Mwanzilishi≠ | Synthesised from cluster randomization methodology (Donner, 1978; Donner & Klar, 2000) and adaptive design frameworks (Bauer & Kohne, 1994; Pallmann et al., 2018) | Abraham Wald (sequential analysis foundation); expanded by Robbins, Armitage, and others |
| Aina≠ | Experimental design | Experimental research design |
| Chanzo asilia≠ | Hayes, R. J., & Moulton, L. H. (2017). Cluster Randomised Trials (2nd ed.). CRC Press / Chapman & Hall. ISBN: 978-1498728225 | Chow, S. C., & Chang, M. (2008). Adaptive Design Methods in Clinical Trials. Chapman and Hall/CRC. ISBN: 978-1584886761 |
| Majina mbadala | adaptive cluster RCT, adaptive group-randomized trial, cluster adaptive design, adaptive cluster trial | adaptive design, response-adaptive randomization, adaptive trial, adaptive randomization |
| Zinazohusiana | 5 | 5 |
| Muhtasari≠ | A cluster randomized adaptive experiment combines two methodological principles: (1) intact groups such as schools, clinics, or villages are randomly assigned to treatment conditions rather than individuals, and (2) pre-specified rules allow the design to be modified during the trial based on accumulating cluster-level data. Adaptations may include dropping underperforming arms, reallocating clusters, or adjusting sample size, while maintaining statistical validity and controlling Type I error. | 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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