限定序数结果下的因果关系概率

Hanmei Sun, Chengfeng Shi, Qiang Zhao
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引用次数: 0

摘要

因果关系概率(PC)通常用于责任评估。例如,在法律方面,当病人服用某种药物后出现副作用并因此起诉制药公司时,因果概率的值可以帮助评估副作用是由药物引起的可能性,换句话说,病人胜诉的可能性有多大。除了法律纠纷问题之外,当人们想要解释其他领域已经发生的事件之间的因果关系时,PC 同样发挥着重要作用。本文首先回顾了二元结果因果关系概率的定义和界限,然后将其推广到序数结果。文章证明,与只考虑暴露变量和结果变量的简单情况相比,在完整的中介分析中加入额外的中介变量信息能提供更精细的界限。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bounding the probability of causality under ordinal outcomes
The probability of causation (PC) is often used in liability assessments. In a legal context, for example, where a patient suffered the side effect after taking a medication and sued the pharmaceutical company as a result, the value of the PC can help assess the likelihood that the side effect was caused by the medication, in other words, how likely it is that the patient will win the case. Beyond the issue of legal disputes, the PC plays an equally large role when one wants to go about explaining causal relationships between events that have already occurred in other areas. This article begins by reviewing the definitions and bounds of the probability of causality for binary outcomes, then generalizes them to ordinal outcomes. It demonstrates that incorporating additional mediator variable information in a complete mediation analysis provides a more refined bound compared to the simpler scenario where only exposure and outcome variables are considered.
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