Regression modelQuasi-experimental / causal inference
面板数据边际结构模型 (MSM)
面板数据边际结构模型 (MSM) 使用跨多个时间段的倾向得分加权（IPTW）来估计时变处理的因果效应，同时恰当地调整受先前处理本身影响的时变混淆因素——这是常规回归无法处理的偏差来源。
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Method map
The neighbourhood of related methods — select a node to explore.
来源
- Robins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550-560. DOI: 10.1097/00001648-200009000-00011 ↗
- Hernan, M. A., & Robins, J. M. (2020). Causal Inference: What If. Chapman & Hall/CRC. link ↗
如何引用本页
ScholarGate. (2026, June 3). Panel Data Marginal Structural Model with Inverse Probability Weighting. ScholarGate. https://scholargate.app/zh/causal-inference/panel-data-marginal-structural-model
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- 逆概率治疗加权法 (IPW / IPTW)因果推断↔ compare
- Marginal Structural Model (MSM)因果推断↔ compare
- 面板数据双重差分法 (Panel DiD / TWFE)因果推断↔ compare
- 面板数据逆概率加权因果推断↔ compare
- 面板数据固定效应模型计量经济学↔ compare