Causal inference in statistics: An overview

Provides a canonical overview or reference point for the relevant DoOperator research area.

A compact overview of structural causal models, graphical assumptions, interventions, counterfactuals, and the role of do-calculus in causal inference.

Use when orienting a new paper, blog post, benchmark, or research plan in this area.

Do not cite the overview as evidence that a specific method works in a specific deployment setting without checking the underlying primary paper.