Comparer des méthodes

	Expérience factorielle complète en double aveugle	Expérience factorielle complète
Domaine	Plans d'expériences	Plans d'expériences
Famille	Process / pipeline	Process / pipeline
Année d'origine	1935 (factorial foundations, Fisher); double-blind combined application from 1950s onward	1926 (Fisher's foundational paper); codified by the 1950s–1960s
Auteur d'origine	Full factorial design: Ronald A. Fisher; double-blind masking: formalized in clinical research mid-20th century	Ronald A. Fisher
Type	Controlled experimental design with masking	Experimental design
Source fondatrice	Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119492443	Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley-Interscience. ISBN: 978-0471718130
Alias	double-masked full factorial design, double-blind complete factorial experiment, blinded full factorial RCT, double-blind factorial trial	full factorial design, complete factorial design, 2^k factorial design, FFD
Apparentées	4	6
Résumé	A double-blind full factorial experiment crosses every level of every independent variable to create all possible treatment combinations, while ensuring that neither participants nor outcome assessors know which condition each participant has been assigned to. This design simultaneously achieves comprehensive examination of main effects and all interactions, and protection against performance and detection bias through blinding — making it especially valuable in clinical, pharmacological, and behavioral research.	A full factorial experiment runs every possible combination of all chosen factor levels, making it the gold standard for simultaneously estimating main effects, two-way interactions, and higher-order interactions among multiple independent variables. Introduced through Ronald Fisher's foundational work on factorial designs in the 1920s and systematised by Box, Hunter, and Montgomery, it provides complete information about how factors act individually and in combination on an outcome.