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| パイロット無作為化比較試験× | 要因ランダム化比較試験(Factorial Randomized Controlled Trial)× | |
|---|---|---|
| 分野 | 実験計画法 | 実験計画法 |
| 系統 | Process / pipeline | Process / pipeline |
| 提唱年≠ | 1990s–2000s (methodological formalization) | 1926 (Fisher factorial foundations); 2000s–2010s (clinical factorial RCT formalization) |
| 提唱者≠ | Formalized through clinical trials methodology community | R. A. Fisher (factorial design foundations); adapted into clinical trials via MOST framework (Collins et al., 2014) |
| 種類≠ | Experimental feasibility design | Experimental trial design |
| 原典≠ | Thabane, L., Ma, J., Chu, R., Cheng, J., Ismaila, A., Rios, L. P., ... & Goldsmith, C. H. (2010). A tutorial on pilot studies: the what, why and how. BMC Medical Research Methodology, 10(1), 1. DOI ↗ | 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 ↗ |
| 別名 | pilot RCT, feasibility RCT, pilot trial, preliminary RCT | Factorial RCT, factorial trial, multi-factor RCT, factorial experiment with randomization |
| 関連≠ | 5 | 6 |
| 概要≠ | A pilot randomized controlled trial (pilot RCT) is a small-scale, fully randomized experiment conducted before a definitive RCT to test the feasibility of study procedures, estimate key parameters such as recruitment rates and effect-size variability, and identify practical barriers. It uses the same randomization, intervention, and measurement protocol as the planned full trial but on a fraction of the target sample. The goal is not to confirm efficacy but to refine and justify the main trial design. | 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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