Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Faktoriālais randomizētais kontrolētais pētījums× | Adaptīvs randomizēts kontrolēts pētījums× | |
|---|---|---|
| Nozare | Eksperimentu plānošana | Eksperimentu plānošana |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 1926 (Fisher factorial foundations); 2000s–2010s (clinical factorial RCT formalization) | 1980s–2000s (formalized; earlier sequential testing roots from Wald, 1947) |
| Autors≠ | R. A. Fisher (factorial design foundations); adapted into clinical trials via MOST framework (Collins et al., 2014) | Donald Berry and others; foundational adaptive trial methods developed through 1980s–2000s biostatistics literature |
| Tips≠ | Experimental trial design | Experimental design — adaptive variant of RCT |
| Pirmavots≠ | 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 ↗ | Chow, S.-C., & Chang, M. (2008). Adaptive Design Methods in Clinical Trials. Chapman & Hall/CRC. ISBN: 978-1584887690 |
| Citi nosaukumi | Factorial RCT, factorial trial, multi-factor RCT, factorial experiment with randomization | Adaptive RCT, Response-adaptive RCT, Adaptive clinical trial, Platform trial |
| Saistītās | 6 | 6 |
| Kopsavilkums≠ | 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. | An adaptive randomized controlled trial (adaptive RCT) is an experimental design in which pre-specified rules allow modifications to the trial while it is ongoing — such as changing allocation ratios, dropping underperforming arms, or stopping early for efficacy or futility — based on accumulating interim data. These adaptations are planned before the trial starts and governed by statistical rules to preserve Type I error control and validity. |
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