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1 Counterfactual and RCTs

1.1-Chapter Introduction

1.2-Potential Outcomes Framework

1.3-Randomized Controlled Trials

1.4-Average Treatment Effects

1.5-Identification Strategies

1.6-Practical Implementation

2 Causal Graphs and SCM

README

3 Python and Regression

3.1-Chapter Introduction

3.2-Regression Quick Start

3.3-OLS Linear Regression

3.4-Logit Regression

3.5-Model Comparison Tables

4 Regression Analysis

4.1-Chapter Introduction

4.2-Simple Linear Regression

4.3-Multiple Regression

4.4-Regression Diagnostics

4.5-Categorical Variables and Interactions

4.6-Interpretation and Reporting

5 Data and Libraries

5.1-Chapter Introduction

5.10-Integrated Workflow

5.2-Data Import and Inspection

5.3-Data Cleaning

5.4-Variable Construction

5.5-Data Transformation

5.6-Merging and Reshaping

5.7-Practical Case Study

5.8-Statsmodels Essentials

5.9-Scipy and Linearmodels

6 Visualization

6.1-Chapter Introduction

6.2-Univariate Visualization

6.3-Bivariate Visualization

6.4-Regression Visualization

6.5-Distribution Comparison

6.6-Publication-Quality Figures

6.7-Chapter Summary

7 Matching and PSM

README

8 IV and 2SLS

README

9 Panel Data and FE

9.1-Chapter Introduction

9.2-Panel Data Basics

9.3-Fixed Effects Models

9.4-Random Effects Models

9.5-Advanced Panel Data Topics

9.6-Summary and Review

10 DID

10.1-Chapter Introduction

10.2-DID Fundamentals

10.3-Parallel Trends Assumption

10.4-Placebo Tests

10.5-Classic Cases and Python Implementation

10.6-Chapter Summary

10.7-Event Study Methodology

11 RDD

11.1-Chapter Introduction

11.2-RDD Fundamentals and Identification

11.3-Continuity Assumption and Validity Tests

11.4-Bandwidth Selection and Robustness Tests

11.5-Classic Cases and Python Implementation

11.6-Chapter Summary

12 Synthetic Control

README

13 HTE and Causal Forest

README

14 DML and Causal AI

README

15 Time Series (Optional)

15.1-Chapter Introduction

15.2-Time Series Basics

15.3-Time Series Decomposition

15.4-ARIMA Models

15.6-Summary and Review

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Matching and PSM

This chapter is coming soon. Please refer to the [Chinese version](/zh/StatsPai/module-7_Matching and PSM/) for now.

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