Probabilities of Causation: Bounds and Identifcation
Probabilities of Causation: Bounds and Identifcation
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因果关系的概率：界限和识别
DOI：
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发表时间：
2000
期刊：
影响因子：
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通讯作者：
Xintao Wu
中科院分区：
文献类型：
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作者：
Lu Zhang;Yongkai Wu;Xintao Wu
本文探讨在给定情境下估计一个事件是另一个事件原因的概率问题。利用必要因果关系或充分因果关系（或两者兼具）概率的结构 - 语义定义，我们展示了在给定关于数据生成过程的各种假设的情况下，如何从实验和观察研究中获得的数据对这些量进行最优界定。特别是，我们通过弱化数据生成假设并推导出因果概率的理论上精确的界限，强化了珀尔（1999）的研究结果。这些结果精确地描述了在统计度量（如超额风险比）可用于评估归因量（如因果概率）之前必须做出的假设。
This paper deals with the problem of estimating the probability that one event was the cause of another in a given scenario. Using structural-semantical de nitions of the probabilities of necessary or su cient causation (or both), we show how to optimally bound these quantities from data obtained in experimental and observational studies, given various assumptions concerning the data-generating process. In particular, we strengthen the results of Pearl (1999) by weakening the data-generation assumptions and deriving theoretically sharp bounds on the probabilities of causation. These results delineate precisely the assumptions that must be made before statistical measures (such as the excess-risk-ratio) could be used for assessing attributional quantities (such as the probability of causation).