方法对比
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| 交叉现场实验× | 现场实验× | |
|---|---|---|
| 领域 | 实验设计 | 实验设计 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1960s–1970s (field experiment framework); crossover application in non-clinical fields from 1980s onward | 1920s–1930s (agriculture); 1990s–2000s (social sciences) |
| 提出者≠ | Crossover design principles attributed to R. A. Fisher (1930s); field experiment tradition developed by Donald T. Campbell and Julian Stanley (1960s) | Formalized by R. A. Fisher (1935); systematized in social sciences by Harrison & List (2004) |
| 类型≠ | Within-subject experimental design conducted in naturalistic settings | Experimental design |
| 开创性文献≠ | Senn, S. (2002). Cross-over Trials in Clinical Research (2nd ed.). John Wiley & Sons. ISBN: 978-0471496533 | Harrison, G. W., & List, J. A. (2004). Field experiments. Journal of Economic Literature, 42(4), 1009–1055. DOI ↗ |
| 别名 | within-subject field experiment, crossover field trial, repeated-measures field experiment, field crossover design | field trial, natural field experiment, randomized field experiment, field RCT |
| 相关 | 5 | 5 |
| 摘要≠ | A crossover field experiment is a within-subject experimental design conducted outside the laboratory in naturalistic, real-world settings. Each participant or unit receives multiple treatments in a randomized sequence, separated by washout periods, allowing researchers to observe causal effects while each unit serves as its own control. This approach combines the internal validity of crossover designs with the ecological validity characteristic of field experimentation. | A field experiment applies the logic of a randomized controlled trial in a naturally occurring, real-world environment rather than an artificial laboratory. Participants are randomly assigned to treatment and control conditions while going about everyday activities, allowing researchers to estimate causal effects with high internal validity while preserving a level of ecological realism that laboratory settings cannot offer. The design is especially prominent in economics, public health, political science, and development research. |
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