因果关系与决策:戴维的“统计因果关系的决策理论基础”

IF 1.7 4区医学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Journal of Causal Inference Pub Date : 2022-01-01 DOI:10.1515/jci-2022-0046

J. Pearl

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引用次数: 4

摘要

在最近一期的本刊中，Philip david(2021)提出了一个基于统计决策理论的因果推理框架，即在许多方面与熟悉的因果图框架(例如，有向无环图(dag))兼容。这篇社论比较了这两种框架的方法论特点及其认识论基础。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Causation and decision: On Dawid’s “Decision theoretic foundation of statistical causality”

Abstract In a recent issue of this journal, Philip Dawid (2021) proposes a framework for causal inference that is based on statistical decision theory and that is, in many aspects, compatible with the familiar framework of causal graphs (e.g., Directed Acyclic Graphs (DAGs)). This editorial compares the methodological features of the two frameworks as well as their epistemological basis.

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来源期刊

Journal of Causal Inference Decision Sciences-Statistics, Probability and Uncertainty

CiteScore

1.90

自引率

14.30%

发文量

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.