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.
翻译:自然实验是观察性研究,将治疗条件分配给不同人群是偶然的,“在野外”出现。来自经济、医疗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测试和因果关系估计,否则,这些结果变量将昂贵、不可行或不道德。本文介绍VAINE(视觉化和自然实验AI),这是一个视觉分析工具,用来从观察数据中识别和了解自然实验。然后我们展示VANE如何被利用来验证因果关系,估计平均治疗效果,并通过两种使用假设来识别辛普森悖论等统计现象。