Initiating R with a Basic Causal Inference Example
As we journey from the theoretical foundations to the empirical applications of causal inference, this chapter marks a significant transition. Herein, we shall dive deep into the utilization of the R programming language as a tool for applying the concepts previously discussed. This chapter caters to both those newly acquainted with R and those seeking to refine their existing knowledge. Our objective is to explain the core principles of R programming within the context of causal analysis.
In this chapter, we start with the basics of R, including setting up your workspace and writing simple scripts. You’ll learn about data types, basic operations, and essential functions in R. We’ll then apply basic causal inference methods using real-world data examples. This includes data preparation, exploratory analysis, implementing simple causal models, and interpreting results. This chapter features carefully selected code snippets...
