Vertaile menetelmiä
Tarkastele valitsemiasi menetelmiä rinnakkain; eroavat rivit korostetaan.
| Klusterirandomoitu kontrolliryhmäkokeellinen asetelma× | Faktoriaalinen satunnaistettu kontrolloitu koe× | |
|---|---|---|
| Tieteenala | Koesuunnittelu | Koesuunnittelu |
| Menetelmäperhe | Process / pipeline | Process / pipeline |
| Syntyvuosi≠ | 1990s (formal methodology development) | 1926 (Fisher factorial foundations); 2000s–2010s (clinical factorial RCT formalization) |
| Kehittäjä≠ | Murray, D. M.; Donner, A. and Klar, N. (systematic formalization) | R. A. Fisher (factorial design foundations); adapted into clinical trials via MOST framework (Collins et al., 2014) |
| Tyyppi≠ | Experimental design | Experimental trial design |
| Alkuperäislähde≠ | Donner, A., & Klar, N. (2000). Design and Analysis of Cluster Randomization Trials in Health Research. Arnold. ISBN: 978-0340691533 | 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 ↗ |
| Rinnakkaisnimet | CRCT with control group, group-randomized trial, cluster RCT control group design, community randomized controlled trial | Factorial RCT, factorial trial, multi-factor RCT, factorial experiment with randomization |
| Liittyvät | 6 | 6 |
| Tiivistelmä≠ | A cluster randomized control group experimental design randomly assigns intact groups (clusters) — such as schools, clinics, or communities — rather than individuals to treatment or control conditions. At least one cluster group receives no active intervention, serving as the control. This design is essential when individual randomization is impractical or contamination between participants in close proximity is likely. | 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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