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| Факториален рандомизиран контролиран експеримент× | Пълен факторен експеримент× | |
|---|---|---|
| Област | Планиране на експеримента | Планиране на експеримента |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1926 (Fisher factorial foundations); 2000s–2010s (clinical factorial RCT formalization) | 1926 (Fisher's foundational paper); codified by the 1950s–1960s |
| Създател≠ | R. A. Fisher (factorial design foundations); adapted into clinical trials via MOST framework (Collins et al., 2014) | Ronald A. Fisher |
| Тип≠ | Experimental trial design | Experimental design |
| Основополагащ източник≠ | 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 ↗ | Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley-Interscience. ISBN: 978-0471718130 |
| Други названия | Factorial RCT, factorial trial, multi-factor RCT, factorial experiment with randomization | full factorial design, complete factorial design, 2^k factorial design, FFD |
| Свързани | 6 | 6 |
| Резюме≠ | 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. | A full factorial experiment runs every possible combination of all chosen factor levels, making it the gold standard for simultaneously estimating main effects, two-way interactions, and higher-order interactions among multiple independent variables. Introduced through Ronald Fisher's foundational work on factorial designs in the 1920s and systematised by Box, Hunter, and Montgomery, it provides complete information about how factors act individually and in combination on an outcome. |
| ScholarGateНабор от данни ↗ |
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