Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Односторонний слепой полнофакторный эксперимент× | Дробный факторный эксперимент× | |
|---|---|---|
| Область | Планирование эксперимента | Планирование эксперимента |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | Full factorial: 1935 (Fisher); single-blind clinical convention: mid-20th century | 1945 (Finney); broader development 1950s–1970s by Box, Hunter |
| Автор метода≠ | Full factorial framework: R. A. Fisher; single-blind masking practice: clinical trial tradition, standardized by the 20th century | D. J. Finney (formal development); foundations in Ronald Fisher's factorial design work |
| Тип≠ | Controlled experimental design | Quantitative experimental design |
| Основополагающий источник≠ | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478 | 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 full factorial, single-blind complete factorial, SB-FFE, single-blind all-combinations design | fractional factorial design, FFD, 2^(k-p) design, fractional replication |
| Связанные≠ | 6 | 4 |
| Сводка≠ | A single-blind full factorial experiment systematically tests every combination of all factor levels while keeping participants unaware of their treatment assignment. This design allows simultaneous estimation of all main effects and all interaction effects between factors, with single-blind masking reducing participant-side biases such as demand characteristics and expectation effects — without requiring investigator blinding. | A fractional factorial experiment is a resource-efficient experimental design that tests only a carefully chosen fraction of all possible factor-level combinations. By exploiting the principle that high-order interactions are usually negligible, it identifies the main effects and low-order interactions of k factors using far fewer runs than a full factorial design — making it the workhorse of industrial and engineering screening experiments. |
| ScholarGateНабор данных ↗ |
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