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Krzyżowe pełne eksperymenty czynnikowe×Jednoczynnikowa ANOVA z powtarzanymi pomiarami×
DziedzinaPlanowanie eksperymentówStatystyka
RodzinaProcess / pipelineHypothesis test
Rok powstaniaMid-to-late 20th century (crossover trials formalised ~1960s–1980s; full factorial DoE from Fisher ~1935)1992
TwórcaDeveloped within the design-of-experiments tradition (R. A. Fisher and successors); crossover adaptation formalised by B. Jones and M. G. KenwardGirden (textbook treatment); Field (2013)
TypWithin-subject full factorial experimental designParametric within-subjects mean comparison
Źródło pierwotneJones, B., & Kenward, M. G. (2003). Design and Analysis of Cross-Over Trials (2nd ed.). Chapman and Hall/CRC. ISBN: 978-1584883429Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed., Ch. 14). SAGE. ISBN: 978-1446249185
Inne nazwywithin-subject full factorial design, repeated-measures full factorial experiment, crossover factorial trial, full factorial crossover designwithin-subjects ANOVA, repeated measures analysis of variance, rm-ANOVA, Tekrarlı Ölçüm ANOVA
Pokrewne64
PodsumowanieA crossover full factorial experiment combines the efficiency of a crossover (within-subject) design with the comprehensiveness of a full factorial design. Every participant receives all combinations of the factor levels across successive treatment periods, separated by washout intervals, allowing complete estimation of all main effects and interactions while using each participant as their own control.Repeated-measures ANOVA is a parametric hypothesis test that compares three or more measurements taken from the same individuals — typically across time points or conditions — to decide whether their means differ. It extends one-way ANOVA to within-subjects designs, as treated in standard references such as Girden (1992) and Field (2013).
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ScholarGatePorównaj metody: Crossover Full Factorial Experiment · Repeated-measures ANOVA. Pobrano 2026-06-19 z https://scholargate.app/pl/compare