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| Клъстерно рандомизиран експеримент с множество рамена× | Многораменен експеримент× | |
|---|---|---|
| Област | Планиране на експеримента | Планиране на експеримента |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1990s–2000s (systematic formalization) | 1990s–2000s (clinical formalization); multi-arm concept implicit in ANOVA-era factorial designs |
| Създател≠ | Building on cluster randomization (Donner & Klar) and multi-arm trial methods developed in clinical and public health research | Developed within clinical trials methodology; formalized by Parmar, Royston and colleagues (UK MRC CTU, early 2000s) |
| Тип | Experimental design | Experimental design |
| Основополагащ източник≠ | Donner, A., & Klar, N. (2000). Design and Analysis of Cluster Randomization Trials in Health Research. Arnold. ISBN: 978-0340691533 | 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 ↗ |
| Други названия | multi-arm cluster RCT, cluster-randomized multi-group trial, multi-arm group-randomized trial, CRCT multi-arm | multi-arm trial, multiple-arm experiment, multi-group experiment, many-arm design |
| Свързани≠ | 6 | 5 |
| Резюме≠ | A cluster randomized multi-arm experiment assigns intact groups — such as schools, clinics, or villages — rather than individuals to three or more experimental conditions simultaneously. Randomization occurs at the cluster level to prevent contamination between arms, while the multi-arm structure allows simultaneous evaluation of several interventions against a common control or each other, improving efficiency over a series of two-arm studies. | 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. |
| ScholarGateНабор от данни ↗ |
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