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Einfaches verblindetes vollständiges faktorielles Experiment×Vollfaktorielle Versuchsplanung×
FachgebietVersuchsplanungVersuchsplanung
FamilieProcess / pipelineProcess / pipeline
EntstehungsjahrFull factorial: 1935 (Fisher); single-blind clinical convention: mid-20th century1926 (Fisher's foundational paper); codified by the 1950s–1960s
UrheberFull factorial framework: R. A. Fisher; single-blind masking practice: clinical trial tradition, standardized by the 20th centuryRonald A. Fisher
TypControlled experimental designExperimental design
Wegweisende QuelleMontgomery, 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
Aliasnamensingle-masked full factorial, single-blind complete factorial, SB-FFE, single-blind all-combinations designfull factorial design, complete factorial design, 2^k factorial design, FFD
Verwandt66
ZusammenfassungA single-blind full factorial experiment systematically tests every combination of all factor levels while keeping participants unaware of their treatment assignment. This design allows simultaneous estimation of all main effects and all interaction effects between factors, with single-blind masking reducing participant-side biases such as demand characteristics and expectation effects — without requiring investigator blinding.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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ScholarGateMethoden vergleichen: Single-blind Full Factorial Experiment · Full Factorial Experiment. Abgerufen am 2026-06-19 von https://scholargate.app/de/compare