Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Адаптивное рандомизированное контролируемое исследование× | Факториальное рандомизированное контролируемое исследование× | |
|---|---|---|
| Область | Планирование эксперимента | Планирование эксперимента |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1980s–2000s (formalized; earlier sequential testing roots from Wald, 1947) | 1926 (Fisher factorial foundations); 2000s–2010s (clinical factorial RCT formalization) |
| Автор метода≠ | Donald Berry and others; foundational adaptive trial methods developed through 1980s–2000s biostatistics literature | R. A. Fisher (factorial design foundations); adapted into clinical trials via MOST framework (Collins et al., 2014) |
| Тип≠ | Experimental design — adaptive variant of RCT | Experimental trial design |
| Основополагающий источник≠ | Chow, S.-C., & Chang, M. (2008). Adaptive Design Methods in Clinical Trials. Chapman & Hall/CRC. ISBN: 978-1584887690 | 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 ↗ |
| Другие названия | Adaptive RCT, Response-adaptive RCT, Adaptive clinical trial, Platform trial | Factorial RCT, factorial trial, multi-factor RCT, factorial experiment with randomization |
| Связанные | 6 | 6 |
| Сводка≠ | 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. | 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. |
| ScholarGateНабор данных ↗ |
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