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Повнофакторний крос-дизайн експерименту×Дисперсійний аналіз повторних вимірювань×
ГалузьПланування експериментуСтатистика
РодинаProcess / pipelineHypothesis test
Рік появиMid-to-late 20th century (crossover trials formalised ~1960s–1980s; full factorial DoE from Fisher ~1935)1992
Автор методуDeveloped 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)
ТипWithin-subject full factorial experimental designParametric within-subjects mean comparison
Основоположне джерелоJones, 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
Інші назвиwithin-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
Пов'язані64
ПідсумокA 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).
ScholarGateНабір даних
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ScholarGateПорівняння методів: Crossover Full Factorial Experiment · Repeated-measures ANOVA. Отримано 2026-06-19 з https://scholargate.app/uk/compare