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.

中文翻译：

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VAINE：自然实验的可视化和人工智能

自然实验是观察性研究，其中将治疗条件分配给不同人群是“在野外”偶然发生的。来自经济学、医疗保健和社会科学等领域的研究人员利用自然实验对治疗和结果变量进行假设检验和因果效应估计，否则这些变量将是昂贵的、不可行的或不道德的。在本文中，我们介绍了 VAINE（自然实验的可视化和人工智能），这是一种可视化分析工具，用于从观察数据中识别和理解自然实验。然后，我们展示了如何使用 VAINE 来验证因果关系，估计平均治疗效果，并通过两个使用场景识别统计现象，例如辛普森悖论。