不可错过！700+ppt《因果推理》课程！杜克大学Fan Li教程

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 treatments

• Chapter 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 estimators

• Chapter 3.6. Causal inference with multiple or continuous treatments

• Chapter 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 stratification

• Chapter 6.1. Instrumental variable (IV), noncompliance in RCT 

• Chapter 6.2. Post-treatment confounding: Principal Stratification

• Chapter 7. Regression discontinuity design (RDD)

• Chapter 8. Panel data: Difference-in-differences (DID) and Synthetic control (SC) 

• Chapter 9. Sequentially ignorable assignments: time-varying treatments

• Chapter 10. 贝叶斯推断因果效应，Bayesian inference for causal effects

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