Topics: causal inference; potential outcomes; directed acyclic graphs; experiments

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Apr 23 (Monday)

Topics:

Due

Readings

• Mastering ‘Metrics, Ch. 1: “Randomized Trials”
• EGAP “10 Things to Know About Causal Inference“
• EGAP “10 Strategies for Figuring out if X Caused Y“

Optional

• EGAP “10 Types of Treatment Effect You Should Know About“
• EGAP “10 Things to Know About the Local Average Treatment Effect“

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Apr 25 (Wednesday)

Topics:

Due

Readings

• Gelman and Hill (2007) “Causal inference using more advanced models”, Chapter 10 in Data Analysis Using Regression and Multilvel/Hierarchical Models.
• Keele (2015) “The Statistics of Causal Inference: A View from Political Methodology” Political Analysis.
• Rohrer (2018) “Thinking Clearly About Correlations and Causation: Graphical Causal Models for Observational Data” Advances in Methods and Practices in Psychological Science

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Apr 27 (Friday)

Topics:

Due

Readings

None