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Experiment factorial fraccionat simple cec×Experiment factorial×
CampDisseny experimentalDisseny experimental
FamíliaProcess / pipelineProcess / pipeline
Any d'origen1940s–1950s (fractional factorial foundations); blinding conventions formalised through 1960s–1980s1926–1935
Autor originalFractional factorial theory: R. L. Plackett & J. P. Burman (1946); single-blinding practice codified in clinical trial methodology (20th century)Ronald A. Fisher
TipusControlled experimental designQuantitative experimental design
Font seminalBox, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley-Interscience. ISBN: 978-0471718130Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗
Àliessingle-masked fractional factorial, single-blind FFD, partially blinded fractional factorial, single-blind 2^(k-p) designfactorial design, factorial ANOVA design, multi-factor experiment, crossed-factor design
Relacionats56
ResumA single-blind fractional factorial experiment studies multiple factors simultaneously by testing only a strategically chosen subset — a fraction — of all possible factor-level combinations, while keeping participants unaware of which treatment condition they receive. This design yields substantial information about main effects and selected interactions at a fraction of the cost of a full factorial experiment, with single-blinding reducing participant-side response bias.A factorial experiment is an experimental design in which two or more independent variables (factors) are manipulated simultaneously, and every combination of their levels is tested. Introduced by Ronald Fisher in the 1920s–1930s, it is the standard approach whenever a researcher needs to detect not only the main effect of each factor but also whether the effect of one factor depends on the level of another — the interaction effect.
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ScholarGateCompara mètodes: Single-blind Fractional Factorial Experiment · Factorial Experiment. Recuperat el 2026-06-19 de https://scholargate.app/ca/compare