Comparer des méthodes

	Expérience factorielle complète en double aveugle	Expérience factorielle fractionnaire
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	1945 (Finney); broader development 1950s–1970s by Box, Hunter
Auteur d'origine	Full factorial design: Ronald A. Fisher; double-blind masking: formalized in clinical research mid-20th century	D. J. Finney (formal development); foundations in Ronald Fisher's factorial design work
Type	Controlled experimental design with masking	Quantitative 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	fractional factorial design, FFD, 2^(k-p) design, fractional replication
Apparentées	4	4
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 fractional factorial experiment is a resource-efficient experimental design that tests only a carefully chosen fraction of all possible factor-level combinations. By exploiting the principle that high-order interactions are usually negligible, it identifies the main effects and low-order interactions of k factors using far fewer runs than a full factorial design — making it the workhorse of industrial and engineering screening experiments.