Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Факторный экспериментальный дизайн с претестом и посттестом× | Полный факторный эксперимент× | |
|---|---|---|
| Область | Планирование эксперимента | Планирование эксперимента |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1963 (canonical formalization) | 1926 (Fisher's foundational paper); codified by the 1950s–1960s |
| Автор метода≠ | Codified by Donald T. Campbell and Julian C. Stanley | Ronald A. Fisher |
| Тип≠ | True experimental design | Experimental design |
| Основополагающий источник≠ | Campbell, D. T., & Stanley, J. C. (1963). Experimental and Quasi-Experimental Designs for Research. Rand McNally. link ↗ | Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley-Interscience. ISBN: 978-0471718130 |
| Другие названия | factorial pre-post design, factorial repeated-measures pretest-posttest design, multi-factor pretest-posttest design, FPPD | full factorial design, complete factorial design, 2^k factorial design, FFD |
| Связанные | 6 | 6 |
| Сводка≠ | A factorial pretest-posttest experimental design combines the simultaneous manipulation of two or more independent variables (factors) with measurement of the dependent variable both before and after treatment. This structure allows researchers to assess the main effect of each factor, all possible interaction effects between factors, and the magnitude of change from pretest to posttest — all within a single, fully randomised experiment. | 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. |
| ScholarGateНабор данных ↗ |
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