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| Expérience factorielle pragmatique× | Plan d'expériences factoriel complet× | |
|---|---|---|
| Domaine | Plans d'expériences | Plans d'expériences |
| Famille≠ | Process / pipeline | Hypothesis test |
| Année d'origine≠ | 2000s–2010s (formal integration) | 1926 |
| Auteur d'origine≠ | Synthesized from pragmatic trial methodology (Schwartz & Lellouch, 1967) and factorial design principles (Fisher, 1935); formalized in clinical research contexts in the 2000s–2010s | R. A. Fisher |
| Type≠ | Experimental trial design | Parametric factorial experiment |
| Source fondatrice≠ | Loudon, 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 |
| Alias | pragmatic factorial trial, pragmatic factorial RCT, real-world factorial design, PFE | factorial experiment, 2^k factorial, full factorial, Faktöriyel Deneme Deseni (Full Factorial, 2^k) |
| Apparentées≠ | 3 | 5 |
| Résumé≠ | A 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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