来自杜克大学Fan Li的简明《因果推理》课程！Chapter 1. Introduction 引言Chapter 2. Randomized experiments 随机实验Chapter 2.1: Fisher's and Neyman's mode of inference Chapter 2.2: Covariate adjustment in RCT Chapter 3. Observational studies with ignorable assignments: single-time treatmentsChapter 3.1. Outcome regression Chapter 3.2. Covariate balance, matching, stratification Chapter 3.3. Propensity score Chapter 3.4. Propensity score weighting: inverse probability weighting and overlap weighting Chapter 3.5. Augmented weighting and double-robust estimatorsChapter 3.6. Causal inference with multiple or continuous treatmentsChapter 4. Heterogenous treatment effects and machine learning 异构治疗效应与机器学习Chapter 5. Sensitivity analysis 敏感性分析Chapter 6. Instrumental variable and principal stratificationChapter 6.1. Instrumental variable (IV), noncompliance in RCT Chapter 6.2. Post-treatment confounding: Principal Stratif
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