方法对比
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| 中断时间序列（ITS）分析× | 多基线设计× | |
|---|---|---|
| 领域≠ | 因果推断 | 实验设计 |
| 方法族≠ | Regression model | Process / pipeline |
| 起源年份≠ | 2002 | 1968 |
| 提出者≠ | Wagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial) | Donald M. Baer, Montrose M. Wolf, Todd R. Risley |
| 类型≠ | Quasi-experimental segmented regression | Single-subject experimental design |
| 开创性文献≠ | Bernal, J. L., Cummins, S., & Gasparrini, A. (2017). Interrupted time series regression for the evaluation of public health interventions: a tutorial. International Journal of Epidemiology, 46(1), 348-355. DOI ↗ | Baer, D. M., Wolf, M. M., & Risley, T. R. (1968). Some current dimensions of applied behavior analysis. Journal of Applied Behavior Analysis, 1(1), 91–97. DOI ↗ |
| 别名≠ | ITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi | MBD, multiple-baseline single-case design, staggered baseline design, multiple-probe design |
| 相关≠ | 5 | 4 |
| 摘要≠ | Interrupted Time Series analysis is a quasi-experimental design that estimates the effect of a single, well-dated intervention by comparing the trajectory of an outcome before and after it occurs. Formalised as segmented regression by Wagner and colleagues (2002) and popularised as a public-health evaluation tutorial by Bernal, Cummins and Gasparrini (2017), it separates the intervention's impact into a change in level and a change in slope. | The multiple baseline design is a single-subject experimental design that demonstrates functional control by introducing an intervention at staggered time points across two or more baselines — typically across different behaviors, individuals, or settings. Because no withdrawal of treatment is required, it is especially suitable when the target behavior is irreversible or when removing an effective intervention would be unethical. |
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