方法对比
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| 实用析因实验× | 全因子实验× | |
|---|---|---|
| 领域 | 实验设计 | 实验设计 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | Fractional factorial designs: 1940s–1950s; pragmatic application: 2000s–2010s | 1926 (Fisher's foundational paper); codified by the 1950s–1960s |
| 提出者≠ | Building on Fisher (1935); pragmatic adaptation by Collins, Murphy & Strecher (2007) via MOST framework | Ronald A. Fisher |
| 类型 | Experimental design | Experimental design |
| 开创性文献≠ | Collins, L. M., Murphy, S. A., & Strecher, V. (2007). The multiphase optimization strategy (MOST) and the sequential multiple assignment randomized trial (SMART): New methods for more potent eHealth interventions. American Journal of Preventive Medicine, 32(5S), S112–S118. DOI ↗ | 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 |
| 别名 | pragmatic FFE, fractional factorial trial, pragmatic factorial design, FFD in pragmatic settings | full factorial design, complete factorial design, 2^k factorial design, FFD |
| 相关≠ | 4 | 6 |
| 摘要≠ | A pragmatic fractional factorial experiment applies fractional factorial design principles to real-world or clinical intervention research, enabling simultaneous evaluation of multiple intervention components in a resource-efficient fraction of the full factorial runs. Popularised through the Multiphase Optimization Strategy (MOST), it identifies which components of a multi-component intervention contribute meaningfully to outcomes before a confirmatory randomized trial is conducted. | 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. |
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