Σύγκριση μεθόδων

	Factorial Randomized Controlled Trial	Σχεδιασμός τυχαιοποιημένης ελεγχόμενης δοκιμής με διασταύρωση
Πεδίο	Πειραματικός Σχεδιασμός	Πειραματικός Σχεδιασμός
Οικογένεια	Process / pipeline	Process / pipeline
Έτος προέλευσης	1926 (Fisher factorial foundations); 2000s–2010s (clinical factorial RCT formalization)	1960s (Grizzle 1965 for statistical foundations); widely used in clinical research since the 1970s
Δημιουργός	R. A. Fisher (factorial design foundations); adapted into clinical trials via MOST framework (Collins et al., 2014)	Early formalized by statisticians including Bradford Hill and colleagues in clinical trials; theoretical framework developed by Grizzle (1965) and later Senn (2002)
Τύπος	Experimental trial design	Experimental within-subject design
Θεμελιώδης πηγή	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.	Senn, S. (2002). Cross-over Trials in Clinical Research (2nd ed.). Wiley. ISBN: 978-0471496533
Εναλλακτικές ονομασίες	Factorial RCT, factorial trial, multi-factor RCT, factorial experiment with randomization	crossover RCT, crossover trial, within-subject RCT, AB/BA crossover design
Συναφείς	6	5
Σύνοψη	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.	A crossover randomized controlled trial (crossover RCT) is an experimental design in which each participant receives all study interventions in a randomized sequence, separated by a washout period. Because every participant serves as their own control, within-subject variability is eliminated from the treatment comparison, yielding greater statistical power per participant than a parallel-group RCT of equal size.