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| Faktorski eksperiment sa više krakova× | Faktorski randomizovani kontrolisani eksperiment× | |
|---|---|---|
| Oblast | Eksperimentalni dizajn | Eksperimentalni dizajn |
| Porodica | Process / pipeline | Process / pipeline |
| Godina nastanka≠ | 1926 (factorial basis); multi-arm factorial trials formalized 1980s–1990s | 1926 (Fisher factorial foundations); 2000s–2010s (clinical factorial RCT formalization) |
| Tvorac≠ | R. A. Fisher (factorial foundations); multi-arm extension established in clinical trial methodology | R. A. Fisher (factorial design foundations); adapted into clinical trials via MOST framework (Collins et al., 2014) |
| Tip≠ | Experimental design | Experimental trial design |
| Temeljni izvor≠ | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119492443 | 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 ↗ |
| Drugi nazivi | multi-arm factorial trial, factorial multi-arm trial, multi-arm factorial experiment, MAFT | Factorial RCT, factorial trial, multi-factor RCT, factorial experiment with randomization |
| Srodne | 6 | 6 |
| Sažetak≠ | 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 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. |
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