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Jednoslepe badanie czynnikowe×Eksperyment pełnoskładnikowy×
DziedzinaPlanowanie eksperymentówPlanowanie eksperymentów
RodzinaProcess / pipelineProcess / pipeline
Rok powstaniaFactorial design: 1926; single-blinding as systematic practice: mid-20th century1926 (Fisher's foundational paper); codified by the 1950s–1960s
TwórcaFisher, R. A. (factorial design); blinding practices formalized in clinical trials literature (20th century)Ronald A. Fisher
TypControlled experimental designExperimental design
Źródło pierwotneMontgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley-Interscience. ISBN: 978-0471718130
Inne nazwysingle-masked factorial trial, single-blind factorial design, SB factorial experimentfull factorial design, complete factorial design, 2^k factorial design, FFD
Pokrewne56
PodsumowanieA single-blind factorial experiment combines factorial design — simultaneously varying two or more independent factors across all their level combinations — with single-blinding, in which participants are unaware of which treatment condition they have been assigned to while researchers and administrators remain unmasked. This design enables efficient estimation of main effects and interactions while reducing participant-side response bias.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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ScholarGatePorównaj metody: Single-blind Factorial Experiment · Full Factorial Experiment. Pobrano 2026-06-18 z https://scholargate.app/pl/compare