反事实与因果推断
Counterfactuals and Causal Inference
Stephen L. Morgan · 初版 2007 年
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“在这部经过全面修订与扩充的 Counterfactuals and Causal Inference 第二版中，结合社会科学、人口学和健康科学的实例，系统阐述了反事实方法在观察性数据分析中的核心特征。本书首先借助潜在结果模型（potential outcome model）和因果图介绍了备选估计技术；随后从潜在结果的视角展示了诸如匹配（matching）和回归（regression）等条件化技术。针对因果暴露的重要决定因素未被观测到的研究情境，备选……”
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正在加载完整评论……
之前在 HN 的因果推断（Causal Inference）框架讨论帖里有人发了这个流程图：https://www.bradyneal.com/which-causal-inference-book（我买了《Counterfactuals and Causal Inference》和《Elements of Causal Inference》，两本都很推荐）。
Someone posted this flowchart in a previous HN thread on Causal Inference frameworks: https://www.bradyneal.com/which-causal-inference-book (I picked up Counterfactuals and Causal Inference and Elements of Causal Inference, and would recommend both).
Gelman 自己（和 Jennifer Hill 合著）的那本书里也有不少因果推断方面的实用好技术。[0] Morgan 和 Winship 写的《Counterfactuals and Causal Inference: Methods and Principles for Social Research》[1] 也很赞。一定要买第二版，比第一版强太多了。[0] http://www.amazon.com/Analysis-Regression-Multilevel-Hierarc...…
Gelman's own book (with Jennifer Hill) also has some good, practical techniques on causal inference. [0] Morgan and Winship's Counterfactuals and Causal Inference: Methods and Principles for Social Research [1] is also really good. Be sure to get the second edition; it's much better than the first. [0] http://www.amazon.com/Analysis-Regression-Multilevel-Hierarc...…
……它回答的那组问题有大概 80% 的重叠（尽管 Pearl 和潜在结果框架 PO 各自都有独占的 20%），但我发现后者的词汇更直观一些。经典书目包括 Morgan 和 Winship 的《Counterfactuals and Causal Inference》，或者 Imbens 和 Rubin 的《Causal Inference for Social Scientists》。至于那篇博文，Pearl 说的没错，因果关系确实需要关于设计的定性假设，来证明研究所需假设的合理性……
…The set of questions it answers are about 80% overlapping (although both Pearl and POs have their own 20%), but I find the vocabulary a little more intuitive. Canonical books include Morgan and Winship "Counterfactuals and Causal Inference" or Imbens and Rubin "Causal Inference for Social Scientists". As to the blog post, Pearl is correct that causality requires qualitative assumptions about design to justify assumptions required to do…
感谢，我之前还不知道这本书。我目前正在啃《Counterfactuals and Causal Inference》（第 2 版），对于想找一本全面入门教材的人，我绝对推荐这本（甚至比 JP 的《Causality》更推荐）。
Thank you, I was not aware of this book. I am currently working my way through the Counterfactuals and Causal Inference (2nd), and I would definitely recommend this book (arguably over JP's Causality) to those who are looking for a comprehensive, introductory text.
……分析最终还是不敌更深入的推敲，暴露出假设里的严重漏洞。就拿《Counterfactuals and Causal Inference》这本书里反复引用的“天主教学校教育对考试成绩的影响”这个经典例子来说吧。后面的章节用越来越精细的技术和关于因果机制更复杂的假设重新审视这个例子，而每一次都会利用技术手段暴露出分析中的缺陷……
…analysis eventually succumbs to a more thorough analysis that uncovers serious issues in the assumptions. Take for instance the running example of catholic schoolings effect on test scores used by the boook Counterfactuals and Causal Inference. Subsequent chapter re-treat this example with increasingly sophisticated techniques and more complex assumptions about causal mechanisms, and each time they uncover a flaw in the analysis using techniques…