قارن الطرق
راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.
| تجربة العوامل الكاملة المتقاطعة× | التجربة العاملية× | |
|---|---|---|
| المجال | التصميم التجريبي | التصميم التجريبي |
| العائلة | Process / pipeline | Process / pipeline |
| سنة النشأة≠ | Mid-to-late 20th century (crossover trials formalised ~1960s–1980s; full factorial DoE from Fisher ~1935) | 1926–1935 |
| صاحب الطريقة≠ | Developed within the design-of-experiments tradition (R. A. Fisher and successors); crossover adaptation formalised by B. Jones and M. G. Kenward | Ronald A. Fisher |
| النوع≠ | Within-subject full factorial experimental design | Quantitative experimental design |
| المصدر التأسيسي≠ | Jones, B., & Kenward, M. G. (2003). Design and Analysis of Cross-Over Trials (2nd ed.). Chapman and Hall/CRC. ISBN: 978-1584883429 | Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗ |
| الأسماء البديلة | within-subject full factorial design, repeated-measures full factorial experiment, crossover factorial trial, full factorial crossover design | factorial design, factorial ANOVA design, multi-factor experiment, crossed-factor design |
| ذات صلة | 6 | 6 |
| الملخص≠ | 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. | 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. |
| ScholarGateمجموعة البيانات ↗ |
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