Regression model
前门调整（前门准则）
前门调整是Judea Pearl于1995年提出的图形化识别策略，它能够通过一个完全中介的变量来恢复处理对结果的因果效应，即使存在一个介于处理和结果之间的未观测混淆变量。当后门准则无法满足（因为混淆变量未被测量）时，它是首选工具。
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Method map
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来源
- Pearl, J. (1995). Causal Diagrams for Empirical Research. Biometrika, 82(4), 669-688. DOI: 10.1093/biomet/82.4.669 ↗
- Pearl, J. (2009). Causality: Models, Reasoning, and Inference (2nd ed.). Cambridge University Press. ISBN: 978-0521895606
如何引用本页
ScholarGate. (2026, June 1). Frontdoor Adjustment (Frontdoor Criterion). ScholarGate. https://scholargate.app/zh/causal-inference/frontdoor-adjustment
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.
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- 因果识别（使用do演算）因果推断↔ compare
- 回归断点设计 (Regression Discontinuity Design, RDD)因果推断↔ compare
- 工具变量法/两阶段最小二乘法 (IV/2SLS)因果推断↔ compare