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Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.

Experimento Fatorial Fracionado Cruzado×Experimento Fatorial Completo×
ÁreaDelineamento experimentalDelineamento experimental
FamíliaProcess / pipelineProcess / pipeline
Ano de origem1950s–1970s (fractional factorial from 1940s; crossover integration from 1960s–1970s)1926 (Fisher's foundational paper); codified by the 1950s–1960s
Autor originalBox, Hunter & Hunter (fractional factorial); Senn & Williams (crossover integration)Ronald A. Fisher
TipoWithin-subject multi-factor experimental designExperimental design
Fonte seminalSenn, S. (2002). Cross-over Trials in Clinical Research (2nd ed.). Wiley. ISBN: 978-0471496533Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley-Interscience. ISBN: 978-0471718130
Outros nomescrossover FF design, within-subject fractional factorial, repeated-measures fractional factorial, crossover FFEfull factorial design, complete factorial design, 2^k factorial design, FFD
Relacionados56
ResumoA 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 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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ScholarGateComparar métodos: Crossover Fractional Factorial Experiment · Full Factorial Experiment. Recuperado em 2026-06-19 de https://scholargate.app/pt/compare