1 Foundations: Potential Outcomes
Class materials
Slides: Module 1
Recording: Module 1, Part 1.1
Recording: Module 1, Part 2.1
Recording: Module 1, Part 2.2
Trivia: Module 1
Textbook reading
Review papers on the Potential Outcomes approach
Holland, P. (1986) “Statistics and Causal Inference” (with discussion), Journal of the American Statistical Association, 81:945-970. - D.B. Rubin discussion - D.R. Cox discussion - C. Glymour discussion - C. Granger discussion - P. Holland rejoinder
Rosenbaum, P.R. (1995) “Discussion of ‘Causal diagrams for empirical research’ by J. Pearl,” Biometrika, 82: 698-699.
Little, R.J.A., Rubin, D.B. (2000) “Causal Effects in Clinical and Epidemiological Studies via Potential Outcomes: Concepts and Analytical Approaches,” Annual Review of Public Health, 21:121-145.
Rubin, D.B. (2005) “Causal inference using potential outcomes: Design, modeling, decisions,” Journal of the American Statistical Association, 100, 322-331.
Hernan, MA (2016) “Does Water Kill?”, Annals of Epidemiology, 26(10)
Dominici F, Bargagli-Stoffi FJ, Mealli F (2021)“From Controlled to Undisciplined Data: Estimating Causal Effects in the Era of Data Science Using a Potential Outcome Framework, Harvard Data Science Review, 3(3).
Seminal papers on the Potential Outcomes approach
Neyman, J. (1923) “On the Application of Probability Theory to Agricultural Experiments. Essay on Principles. Section 9.” (translated and edited by D.M. Dabrowska and T.P. Speed, with discussion), in Statistical Science (1990), 5:463-472. - Introduction by T.P. Speed, Editor, Statistical Science
Rubin, D.B. (1974) “Estimating Causal Effects of Treatments in Randomized and Nonrandomized Studies,” Journal of Educational Psychology, 1974; 66: 688-701. [open access]
Rubin, D.B. (1978) “Bayesian Inference for Causal Effects: The Role of Randomization,” Annals of Statistics, 6:34-58.
Rubin, D.B. (1990) “Comment: Neyman (1923) and Causal Inference in Experiments and Observational Studies,” Statistical Science, 5: 472-480.