Implementing Doubly Robust Estimation
This chapter focuses on doubly robust (DR) estimation. This technique, when used in causal analysis, uses two models: one for treatment and one for the outcome. The strength of DR estimation lies in its ability to provide reliable results, even if one of the models isn’t perfect. We’ll break down the theory behind this method and show you how to apply it using R. Starting with the basics, we’ll move on to more advanced techniques and compare DR estimation with other methods, delineating why it’s such a dependable approach. By the end of this chapter, you’ll know how to use DR estimation to get accurate and robust results in your data analysis.
We’ll cover the following topics:
- What is doubly robust estimation?
- Doubly robust estimation in R
- Discussing doubly robust methods
