Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Кластерне рандомізоване факторне дослідження× | Факторне рандомізоване контрольоване дослідження× | |
|---|---|---|
| Галузь | Планування експерименту | Планування експерименту |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 1990s (formalized in group-randomized trial literature) | 1926 (Fisher factorial foundations); 2000s–2010s (clinical factorial RCT formalization) |
| Автор методу≠ | David M. Murray and colleagues; Allan Donner & Neil Klar | R. A. Fisher (factorial design foundations); adapted into clinical trials via MOST framework (Collins et al., 2014) |
| Тип≠ | Experimental design | Experimental trial design |
| Основоположне джерело≠ | Murray, D. M. (1998). Design and Analysis of Group-Randomized Trials. Oxford University Press. ISBN: 978-0195120912 | 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 ↗ |
| Інші назви | cluster-randomized factorial design, group-randomized factorial trial, CRT factorial, clustered factorial experiment | Factorial RCT, factorial trial, multi-factor RCT, factorial experiment with randomization |
| Пов'язані≠ | 5 | 6 |
| Підсумок≠ | A cluster randomized factorial experiment assigns intact groups (clusters such as schools, clinics, or communities) at random to all combinations of two or more treatment factors, enabling simultaneous evaluation of multiple interventions and their interactions while respecting the natural grouping of participants. It merges the logistical and ethical advantages of cluster randomization with the efficiency of factorial design. | 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. |
| ScholarGateНабір даних ↗ |
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