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| Експеримент с пълен факторен дизайн тип кросоувър× | ANOVA с повтарящи се измервания× | |
|---|---|---|
| Област≠ | Планиране на експеримента | Статистика |
| Семейство≠ | Process / pipeline | Hypothesis test |
| Година на възникване≠ | Mid-to-late 20th century (crossover trials formalised ~1960s–1980s; full factorial DoE from Fisher ~1935) | 1992 |
| Създател≠ | Developed within the design-of-experiments tradition (R. A. Fisher and successors); crossover adaptation formalised by B. Jones and M. G. Kenward | Girden (textbook treatment); Field (2013) |
| Тип≠ | Within-subject full factorial experimental design | Parametric within-subjects mean comparison |
| Основополагащ източник≠ | Jones, B., & Kenward, M. G. (2003). Design and Analysis of Cross-Over Trials (2nd ed.). Chapman and Hall/CRC. ISBN: 978-1584883429 | Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed., Ch. 14). SAGE. ISBN: 978-1446249185 |
| Други названия | within-subject full factorial design, repeated-measures full factorial experiment, crossover factorial trial, full factorial crossover design | within-subjects ANOVA, repeated measures analysis of variance, rm-ANOVA, Tekrarlı Ölçüm ANOVA |
| Свързани≠ | 6 | 4 |
| Резюме≠ | A 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). |
| ScholarGateНабор от данни ↗ |
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