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Expérience factorielle pragmatique×Plan d'expériences factoriel complet×
DomainePlans d'expériencesPlans d'expériences
FamilleProcess / pipelineHypothesis test
Année d'origine2000s–2010s (formal integration)1926
Auteur d'origineSynthesized from pragmatic trial methodology (Schwartz & Lellouch, 1967) and factorial design principles (Fisher, 1935); formalized in clinical research contexts in the 2000s–2010sR. A. Fisher
TypeExperimental trial designParametric factorial experiment
Source fondatriceLoudon, K., Treweek, S., Sullivan, F., Donnan, P., Thorpe, K. E., & Zwarenstein, M. (2015). The PRECIS-2 tool: designing trials that are fit for purpose. BMJ, 350, h2147. DOI ↗Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley. ISBN: 978-0471718130
Aliaspragmatic factorial trial, pragmatic factorial RCT, real-world factorial design, PFEfactorial experiment, 2^k factorial, full factorial, Faktöriyel Deneme Deseni (Full Factorial, 2^k)
Apparentées35
RésuméA pragmatic factorial experiment combines two powerful methodological frameworks: the factorial experimental design — which tests multiple intervention components simultaneously — and the pragmatic trial orientation, which prioritizes real-world applicability, broad eligibility criteria, and flexible delivery conditions. The result is a design that efficiently evaluates which components of a complex intervention work, and whether they interact, while maintaining ecological validity for health, behavioral, and educational research.A full factorial design is a parametric experimental method in which every combination of factor levels is tested simultaneously, enabling the estimation of all main effects and all interaction effects in a single study. Rooted in R. A. Fisher's foundational work on designed experiments (1926) and systematically developed by Box, Hunter, and Hunter (2005) and Montgomery (2017), the 2^k form tests k two-level factors across 2^k experimental runs and is the benchmark against which all other factorial designs are measured.
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ScholarGateComparer des méthodes: Pragmatic Factorial Experiment · Full Factorial Design. Consulté le 2026-06-19 sur https://scholargate.app/fr/compare