方法对比
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| 交叉自然实验× | 交叉现场实验× | |
|---|---|---|
| 领域 | 实验设计 | 实验设计 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | Crossover designs: mid-20th century; applied to natural experiments: 1990s–2000s | 1960s–1970s (field experiment framework); crossover application in non-clinical fields from 1980s onward |
| 提出者≠ | Drawn from crossover trial methods (Jones & Kenward) and natural experiment tradition (Mill, 1843; Dunning, 2012) | Crossover design principles attributed to R. A. Fisher (1930s); field experiment tradition developed by Donald T. Campbell and Julian Stanley (1960s) |
| 类型≠ | Quasi-experimental design | Within-subject experimental design conducted in naturalistic settings |
| 开创性文献≠ | Dunning, T. (2012). Natural Experiments in the Social Sciences: A Design-Based Approach. Cambridge University Press. ISBN: 978-1107698000 | Senn, S. (2002). Cross-over Trials in Clinical Research (2nd ed.). John Wiley & Sons. ISBN: 978-0471496533 |
| 别名≠ | within-unit natural experiment, reversal natural experiment, crossover quasi-experiment | within-subject field experiment, crossover field trial, repeated-measures field experiment, field crossover design |
| 相关 | 5 | 5 |
| 摘要≠ | A crossover natural experiment exploits an externally imposed condition — a policy change, law, or environmental event — that exposes the same units (individuals, regions, firms) to both treatment and control states at different times. By observing each unit in multiple conditions, researchers use within-unit variation to estimate causal effects without researcher-controlled randomization, combining the internal validity advantage of crossover designs with the real-world relevance of natural experiments. | 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. |
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