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Imputation approaches for potential outcomes in causal inference

机译:因果推理中潜在结果的归因方法

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摘要

Background: The fundamental problem of causal inference is one of missing data, and specifically of missing potential outcomes: if potential outcomes were fully observed, then causal inference could be made trivially. Though often not discussed explicitly in the epidemiological literature, the connections between causal inference and missing data can provide additional intuition.
机译:背景:因果推理的根本问题是缺少数据之一,尤其是缺少潜在结果:如果完全观察到潜在结果,则可以轻而易举地进行因果推理。尽管在流行病学文献中通常没有明确讨论,但因果推断与缺失数据之间的联系可以提供额外的直觉。

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