เปรียบเทียบวิธี

	การทดลองแบบสุ่มและมีกลุ่มควบคุมแบบปรับเปลี่ยนได้	การทดลองแบบสุ่มที่มีปัจจัยหลายตัวประกอบ
สาขาวิชา	การออกแบบการทดลอง	การออกแบบการทดลอง
ตระกูล	Process / pipeline	Process / pipeline
ปีกำเนิด	1980s–2000s (formalized; earlier sequential testing roots from Wald, 1947)	1926 (Fisher factorial foundations); 2000s–2010s (clinical factorial RCT formalization)
ผู้ริเริ่ม	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)
ประเภท	Experimental design — adaptive variant of RCT	Experimental trial design
แหล่งต้นตำรับ	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.
ชื่อเรียกอื่น	Adaptive RCT, Response-adaptive RCT, Adaptive clinical trial, Platform trial	Factorial RCT, factorial trial, multi-factor RCT, factorial experiment with randomization
ที่เกี่ยวข้อง	6	6
สรุป	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.