16. Regression Discontinuity, Matching, and Uplift in R
Chapter 15 covered A/B testing and predictive modeling. This chapter covers R implementation for the last subsection of the book on causal inference methods—that is, the implementation in R of difference-in-difference (DID) modeling, regression discontinuity (RD), statistical matching, and uplift modeling, discussed in Chapters 10–13. We’ll work with the Lalonde data set, which contains data from an experimental jobs program described in Chapter 13, for statistical matching and uplift modeling.
By the end of the chapter, you will be able to:
Estimate a difference-in-difference model.
Remove the effects of seasonality.
Calculate the effect size in a regression discontinuity or interrupted ...
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