Causal Inference in R

Table of Contents

1. Introducing Causal Inference
2. Unraveling Confounding and Associations
3. Initiating R with a Basic Causal Inference Example
4. Constructing Causality Models with Graphs
5. Navigating Causal Inference through Directed Acyclic Graphs
6. Employing Propensity Score Techniques
7. Employing Regression Approaches for Causal Inference
8. Executing A/B Testing and Controlled Experiments
9. Implementing Doubly Robust Estimation
10. Analyzing Instrumental Variables
11. Investigating Mediation Analysis
12. Exploring Sensitivity Analysis
13. Scrutinizing Heterogeneity in Causal Inference
14. Harnessing Causal Forests and Machine Learning Methods
15. Implementing Causal Discovery in R