Introduction to causal inference
Content
- Introduction to causal inference
Learning objectives
At the end of the session, students should be capable of
- understanding the importance of listing potential confounders
- determining which variables to control for (confounders vs colliders)
- drawing a directed acyclic graph describing the interrelation between variables
- explaining the differences between experimental and observational studies for studying mediation
Readings
- Chapter 2 of VanderWeele (2015)
- Section 13.1 of the course notes
Andrew Heiss’ course notes on directed acyclic graphs (DAG) and types of association.
The structural equation modelling (SEM) approach to mediation
- Paper popularizing linear mediation (Baron & Kenny, 1986)
- Limitations of the linear mediation model approach (Bullock et al., 2010)
The causal inference approach
Complementary readings
Slides
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References
Baron, R., & Kenny, D. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182. https://doi.org/10.1037/0022-3514.51.6.1173
Bullock, J. G., Green, D. P., & Ha, S. E. (2010). Yes, but what’s the mechanism? (Don’t expect an easy answer). Journal of Personality and Social Psychology, 98(4), 550–558. https://doi.org/10.1037/a0018933
Imai, K., Keele, L., & Tingley, D. (2010). A general approach to causal mediation analysis. Psychological Methods, 15(4), 309–334. https://doi.org/10.1037/a0020761
Pearl, J. (2014). Interpretation and identification of causal mediation. Psychological Methods, 19(4), 459–481. https://doi.org/10.1037/a0036434
Pearl, J., Glymour, M., & Jewell, N. (2016). Causal inference in statistics: A primer. Wiley.
Rohrer, J. M. (2018). Thinking clearly about correlations and causation: Graphical causal models for observational data. Advances in Methods and Practices in Psychological Science, 1(1), 27–42. https://doi.org/10.1177/2515245917745629
VanderWeele, T. (2015). Explanation in causal inference: Methods for mediation and interaction. Oxford University Press.