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Faktoriális törtkísérlet átfedéses elrendezésben×Faktoriális kísérlet×
TudományterületKísérlettervezésKísérlettervezés
MódszercsaládProcess / pipelineProcess / pipeline
Keletkezés éve1950s–1970s (fractional factorial from 1940s; crossover integration from 1960s–1970s)1926–1935
MegalkotóBox, Hunter & Hunter (fractional factorial); Senn & Williams (crossover integration)Ronald A. Fisher
TípusWithin-subject multi-factor experimental designQuantitative experimental design
AlapműSenn, S. (2002). Cross-over Trials in Clinical Research (2nd ed.). Wiley. ISBN: 978-0471496533Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗
Alternatív nevekcrossover FF design, within-subject fractional factorial, repeated-measures fractional factorial, crossover FFEfactorial design, factorial ANOVA design, multi-factor experiment, crossed-factor design
Kapcsolódó56
ÖsszefoglalóA crossover fractional factorial experiment is a within-subject design in which each participant receives a strategically chosen subset of all possible factor-level combinations in a defined sequence, with washout periods between treatment periods. By combining the run-economy of fractional factorial designs with the within-subject efficiency of crossover designs, it allows estimation of main effects and selected interactions while controlling for between-subject variability using far fewer participants and experimental runs than a full factorial crossover.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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ScholarGateMódszerek összehasonlítása: Crossover Fractional Factorial Experiment · Factorial Experiment. Letöltve 2026-06-19, forrás: https://scholargate.app/hu/compare