Vertaile menetelmiä
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| Blocked Randomized Controlled Trial× | Faktoriaalinen satunnaistettu kontrolloitu koe× | |
|---|---|---|
| Tieteenala | Koesuunnittelu | Koesuunnittelu |
| Menetelmäperhe | Process / pipeline | Process / pipeline |
| Syntyvuosi≠ | 1920s (Fisher's blocking principle); applied to RCTs from the 1940s onward | 1926 (Fisher factorial foundations); 2000s–2010s (clinical factorial RCT formalization) |
| Kehittäjä≠ | R. A. Fisher (blocking principle); systematic RCT application by Bradford Hill and later Pocock, Friedman et al. | R. A. Fisher (factorial design foundations); adapted into clinical trials via MOST framework (Collins et al., 2014) |
| Tyyppi≠ | Experimental design | Experimental trial design |
| Alkuperäislähde≠ | Friedman, L. M., Furberg, C. D., DeMets, D. L., Reboussin, D. M., & Granger, C. B. (2010). Fundamentals of Clinical Trials (4th ed.). Springer. ISBN: 978-1441915856 | 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 | blocked RCT, block-randomized trial, stratified block randomization trial, permuted block randomization | Factorial RCT, factorial trial, multi-factor RCT, factorial experiment with randomization |
| Liittyvät≠ | 5 | 6 |
| Tiivistelmä≠ | A blocked randomized controlled trial (blocked RCT) uses permuted-block randomization to ensure that treatment groups remain balanced in size — and optionally in key characteristics — throughout recruitment. Within each block of fixed or randomly varied size, all treatment allocations are present in equal numbers, so imbalance cannot accumulate even if the trial is stopped early. This makes blocked RCTs the standard randomization approach in clinical and behavioral intervention research. | 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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