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Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Факторен многораменен експеримент× | Многораменен експеримент× | |
|---|---|---|
| Област | Планиране на експеримента | Планиране на експеримента |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1926 (factorial basis); multi-arm factorial trials formalized 1980s–1990s | 1990s–2000s (clinical formalization); multi-arm concept implicit in ANOVA-era factorial designs |
| Създател≠ | R. A. Fisher (factorial foundations); multi-arm extension established in clinical trial methodology | Developed within clinical trials methodology; formalized by Parmar, Royston and colleagues (UK MRC CTU, early 2000s) |
| Тип | Experimental design | Experimental design |
| Основополагащ източник≠ | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119492443 | 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 factorial trial, factorial multi-arm trial, multi-arm factorial experiment, MAFT | multi-arm trial, multiple-arm experiment, multi-group experiment, many-arm design |
| Свързани≠ | 6 | 5 |
| Резюме≠ | A factorial multi-arm experiment simultaneously tests multiple factors (each at two or more levels) by assigning participants to distinct arms that represent unique combinations of those factors. This design efficiently estimates the independent main effects of each factor and their interactions, all within a single study — making it far more informative than running separate one-factor experiments. | 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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