统计因果关系的潜在结果和决策理论基础

IF 1.7 4区 医学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Journal of Causal Inference Pub Date : 2023-01-01 DOI:10.1515/jci-2022-0012
Thomas S. Richardson, James M. Robins
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引用次数: 2

摘要

在最近发表在该杂志上的一篇文章中,Philip david描述了一个基于决策图的图形因果模型。本文描述了单世界干预图(swg)与这些图的关系。通过这种方式,david的方法与那些基于潜在结果(如Robins的最佳完全随机因果解释结构树图)的方法之间建立了对应关系。更详细地说,给出了david理论的一个重新表述,本质上等同于他的提议,并且与swg同构。
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Potential outcome and decision theoretic foundations for statistical causality
Abstract In a recent work published in this journal, Philip Dawid has described a graphical causal model based on decision diagrams. This article describes how single-world intervention graphs (SWIGs) relate to these diagrams. In this way, a correspondence is established between Dawid's approach and those based on potential outcomes such as Robins’ finest fully randomized causally interpreted structured tree graphs. In more detail, a reformulation of Dawid s theory is given that is essentially equivalent to his proposal and isomorphic to SWIGs.
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来源期刊
Journal of Causal Inference
Journal of Causal Inference Decision Sciences-Statistics, Probability and Uncertainty
CiteScore
1.90
自引率
14.30%
发文量
15
审稿时长
86 weeks
期刊介绍: Journal of Causal Inference (JCI) publishes papers on theoretical and applied causal research across the range of academic disciplines that use quantitative tools to study causality.
期刊最新文献
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