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Expérience factorielle complète par croisement×Expérience factorielle complète×
DomainePlans d'expériencesPlans d'expériences
FamilleProcess / pipelineProcess / pipeline
Année d'origineMid-to-late 20th century (crossover trials formalised ~1960s–1980s; full factorial DoE from Fisher ~1935)1926 (Fisher's foundational paper); codified by the 1950s–1960s
Auteur d'origineDeveloped within the design-of-experiments tradition (R. A. Fisher and successors); crossover adaptation formalised by B. Jones and M. G. KenwardRonald A. Fisher
TypeWithin-subject full factorial experimental designExperimental design
Source fondatriceJones, B., & Kenward, M. G. (2003). Design and Analysis of Cross-Over Trials (2nd ed.). Chapman and Hall/CRC. ISBN: 978-1584883429Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley-Interscience. ISBN: 978-0471718130
Aliaswithin-subject full factorial design, repeated-measures full factorial experiment, crossover factorial trial, full factorial crossover designfull factorial design, complete factorial design, 2^k factorial design, FFD
Apparentées66
RésuméA crossover full factorial experiment combines the efficiency of a crossover (within-subject) design with the comprehensiveness of a full factorial design. Every participant receives all combinations of the factor levels across successive treatment periods, separated by washout intervals, allowing complete estimation of all main effects and interactions while using each participant as their own control.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.
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ScholarGateComparer des méthodes: Crossover Full Factorial Experiment · Full Factorial Experiment. Consulté le 2026-06-19 sur https://scholargate.app/fr/compare