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      <description>读 causalmlbook 的笔记：RCT 中的回归调整与稳健标准误，以及用于处理效应异质性（CATE/HTE）的因果树、因果森林与 honest tree 思路。</description>
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      <title>因果推断笔记：Causal ML Book 第 16 章 反事实框架与 Rubin 因果模型</title>
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      <description>读 Causal Inference and Machine Learning 在线书第 16 章 Counterfactual Framework 的笔记：可操纵性、潜在结果、RCM 假设与「简单组间差」相对 ATE 的偏差分解。</description>
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