**Spring 2017, Columbia University**

**David M. Blei**

Day/Time: Wednesdays, 2:10PM - 4:00PM

Location: 302 Fayerweather

- Introduction and logistics
- Potential outcomes
- S. Morgan and C. Winship. Counterfactuals and Causal Inference. Cambridge University Press, 2nd edition, 2015; Chapter 2.
- G. Imbens and D. Rubin. Causal Inference in Statistics, Social and Biomedical Sciences: An Introduction. Cambridge University Press, 2015; Chapter 1. (optional)
- Causal graphs
- S. Morgan and C. Winship. Counterfactuals and Causal Inference. Cambridge University Press, 2nd edition, 2015; Chapter 3.
- J. Pearl. Causal inference in statistics: An overview. Statistical Surveys, 2009.
- Causal graphs
- S. Morgan and C. Winship. Counterfactuals and Causal Inference. Cambridge University Press, 2nd edition, 2015; Chapter 4.
- Causal graphs and estimation
- J. Pearl. Causality: Models, Reasoning, and Inference,
2nd Edition, Cambridge University Press, 2009; Chapter 3.1, 3.2,
3.3.

- C. Shalizi. Advanced Data Analysis from an Elementary Point of View, 2017; Chapter 24 (except 24.2)
- Bayesian inference, potential outcomes, and randomization
- G. Imbens and D. Rubin. Causal Inference in Statistics, Social and Biomedical Sciences: An Introduction. Cambridge University Press, 2015; Chapter 8.
- D. Rubin. Bayesian inference for causal effects: The role of randomization. The Annals of Statistics, 6(1):34–58, 1978; (optional).
- Bayesian inference, potential outcomes, and observational data
- G. Imbens and D. Rubin. Causal Inference in Statistics, Social and Biomedical Sciences: An Introduction. Cambridge University Press, 2015; Chapter 12.
- A. Gelman, J. Carlin, H. Stern, D. Dunson, A. Vehtari, and D. Rubin. Bayesian Data Analysis. Chapman & Hall/CRC, 3rd edition, 2014; Chapter 8 (optional).
- Double robustness
- G. Imbens and D. Rubin. Causal Inference in Statistics, Social and Biomedical Sciences: An Introduction. Cambridge University Press, 2015; Chapter 18.
- Instrumental variables
- S. Morgan and C. Winship. Counterfactuals and Causal Inference. Cambridge University Press, 2nd edition, 2015; Chapter 9.
- Counterfactuals
- J. Pearl. Causality: Models, Reasoning, and Inference, 2nd Edition, Cambridge University Press, 2009; Chapter 7
- Genetic association
- M. Song, W. Hao, and J. Storey. Testing for genetic association in arbitrarily structured populations. Nature Genetics, 2015. [Supplement]
- Special Guest: Andrew Gelman
- A. Gelman. Causality and statistical learning. American Journal of Sociology, 117(3):955–966, 2011.
- A. Gelman. Experimental reasoning in social science. In Field Experiments and their Critics. Yale University Press, 2010.
- Causality and medicine
- P. Schulam and S. Saria. What-if reasoning with counterfactual Gaussian processes. arXiv 1703.10651, 2017.