In this session, we will talk about non-linear relations between our outcome and covariates, and how we can include polynomials to create a better fitting model. We will also start diving into Causal Inference: Potential outcomes framework, the fundamental problem of causal inference, causal estimands, and study design.
Angrist & Pischke. (2015). “Mastering Metrics”. Chapter 1: Randomized Trials. Pg. 1-11.
Marginal Revolution University. (2019). “Ceteris Paribus: Public vs. Private University”. Video materials from Mastering Metrics.
Download the R Script for the in-class exercise here:
Here is the full R script for this class, with some additional questions: