Rubin causal model

Summary

The Rubin causal model, or potential outcomes framework, defines causal effects by comparing the outcomes that the same unit would have under different treatments. Each unit has one potential outcome for each treatment, but only the one for the treatment actually received is observed. Causal effects such as the average treatment effect are then parameters of the joint distribution of potential outcomes. The framework goes back to Jerzy Neyman's work on experiments and was developed by Donald Rubin for observational studies. It is a basic language of causal inference.