Causal effect estimation: Basic methodologies

In this chapter, we provide a comprehensive review of causal inference methods for the causal effect estimation task under the potential outcome framework, one of the well-known causal inference frameworks. The methods are divided into two categories depending on whether they require all three assumptions of the potential outcome framework or not. For each category, both the traditional statistical methods and the recent machine learning enhanced methods are discussed and compared. Most contents in this chapter are reprinted from our work (Yao et al. (ACM Trans Knowl Discov Data 15(5):1-46, 2021)).