VAINE: Visualization and AI for Natural Experiments
Not on the map. Why?
Abstract (arXiv)
Natural experiments are observational studies where the assignment of treatment conditions to different populations occurs by chance "in the wild". Researchers from fields such as economics, healthcare, and the social sciences leverage natural experiments to conduct hypothesis testing and causal effect estimation for treatment and outcome variables that would otherwise be costly, infeasible, or unethical. In this paper, we introduce VAINE (Visualization and AI for Natural Experiments), a visual analytics tool for identifying and understanding natural experiments from observational data. We then demonstrate how VAINE can be used to validate causal relationships, estimate average treatment effects, and identify statistical phenomena such as Simpson's paradox through two usage scenarios.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Sep 2021.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 0; 2023: 3; 2024: 0; 2025: 1; 2026: 1.
6 papers.
- 2023An Explainable AI Approach to Large Language Model Assisted Causal Model Auditing and Developmentcited by 5
- 2023SuperNOVA: Design Strategies and Opportunities for Interactive Visualization in Computational Notebookscited by 3
- 2021Identifying Causal Influences on Publication Trends and Behavior: A Case Study of the Computational Linguistics Communitycited by 1
- 2023VISPUR: Visual Aids for Identifying and Interpreting Spurious Associations in Data-Driven Decisionscited by 1
- 2026De-paradox Tree: Breaking Down Simpson's Paradox via A Kernel-Based Partition Algorithmcited by 1
- 2025XplainAct: Visualization for Personalized Intervention Insightscited by 0
- 2026De-paradox Tree: Breaking Down Simpson's Paradox via A Kernel-Based Partition Algorithm2 Mar 2026
- 2025XplainAct: Visualization for Personalized Intervention Insights19 Jul 2025
- 2023An Explainable AI Approach to Large Language Model Assisted Causal Model Auditing and Development23 Dec 2023
- 2023VISPUR: Visual Aids for Identifying and Interpreting Spurious Associations in Data-Driven Decisions26 Jul 2023
- 2023SuperNOVA: Design Strategies and Opportunities for Interactive Visualization in Computational Notebooks4 May 2023
- 2021Identifying Causal Influences on Publication Trends and Behavior: A Case Study of the Computational Linguistics Community15 Oct 2021