Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Экспериментальный дизайн с факторным контрольным условием× | Факториальное рандомизированное контролируемое исследование× | |
|---|---|---|
| Область | Планирование эксперимента | Планирование эксперимента |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1926–1935 | 1926 (Fisher factorial foundations); 2000s–2010s (clinical factorial RCT formalization) |
| Автор метода≠ | Ronald A. Fisher | R. A. Fisher (factorial design foundations); adapted into clinical trials via MOST framework (Collins et al., 2014) |
| Тип≠ | Experimental design | Experimental trial design |
| Основополагающий источник≠ | Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗ | Collins, L. M., Dziak, J. J., Kugler, K. C., & Trail, J. B. (2014). Factorial experiments: Efficient tools for evaluation of intervention components. American Journal of Preventive Medicine, 47(4), 498–504. DOI ↗ |
| Другие названия | factorial controlled experiment, factorial design with control, factorial RCT with control arm, multi-factor controlled experiment | Factorial RCT, factorial trial, multi-factor RCT, factorial experiment with randomization |
| Связанные | 6 | 6 |
| Сводка≠ | A factorial control group experimental design crosses two or more independent variables (factors) in a fully factorial structure while including at least one condition that serves as a no-treatment or standard-treatment control. This allows researchers to simultaneously estimate the main effect of each factor, their interactions, and the size of those effects relative to a meaningful baseline, maximising both causal precision and experimental efficiency. | A factorial randomized controlled trial (factorial RCT) is an experimental design in which participants are randomly assigned to every possible combination of two or more independent factors (treatments or intervention components) simultaneously. This allows researchers to estimate the main effect of each factor and their interactions within a single, efficient trial, rather than running separate experiments for each factor. |
| ScholarGateНабор данных ↗ |
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