Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Односторонний дробный факторный эксперимент× | Полный факторный эксперимент× | |
|---|---|---|
| Область | Планирование эксперимента | Планирование эксперимента |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1940s–1950s (fractional factorial foundations); blinding conventions formalised through 1960s–1980s | 1926 (Fisher's foundational paper); codified by the 1950s–1960s |
| Автор метода≠ | Fractional factorial theory: R. L. Plackett & J. P. Burman (1946); single-blinding practice codified in clinical trial methodology (20th century) | Ronald A. Fisher |
| Тип≠ | Controlled experimental design | Experimental design |
| Основополагающий источник | 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 | 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 | single-masked fractional factorial, single-blind FFD, partially blinded fractional factorial, single-blind 2^(k-p) design | full factorial design, complete factorial design, 2^k factorial design, FFD |
| Связанные≠ | 5 | 6 |
| Сводка≠ | A single-blind fractional factorial experiment studies multiple factors simultaneously by testing only a strategically chosen subset — a fraction — of all possible factor-level combinations, while keeping participants unaware of which treatment condition they receive. This design yields substantial information about main effects and selected interactions at a fraction of the cost of a full factorial experiment, with single-blinding reducing participant-side response bias. | 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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