Potential outcome and decision theoretic foundations for statistical causality-Reference-Cited by-同舟云学术

Potential outcome and decision theoretic foundations for statistical causality

Published:2023-01-01 Issue:1 Volume:11 Page:
ISSN:2193-3685
Container-title:Journal of Causal Inference
language:en
Short-container-title:

Author:

Richardson Thomas S.¹,Robins James M.²

Affiliation:

1. Department of Statistics, University of Washington , Seattle , Washington , United States

2. Department of Epidemiology, Harvard School of Public Health , Boston , United States

Abstract

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.

Publisher

Walter de Gruyter GmbH

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.degruyter.com/document/doi/10.1515/jci-2022-0012/pdf

Reference23 articles.

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2. Robins JM. A new approach to causal inference in mortality studies with sustained exposure periods - application to control of the healthy worker survivor effect. Math Model. 1986;7:1393–512.

3. Richardson TS, Robins JM. Single world intervention graphs (SWIGs): A unification of the counterfactual and graphical approaches to causality. Center for Statistics and the Social Sciences Technical Report. 2013. University of Washington, Seattle, Washington, USA. https://www.csss.washington.edu/Papers/wp128.pdf.

4. Robins JM, Richardson TS. Alternative graphical causal models and the identification of direct effects. Causality and psychopathology: finding the determinants of disorders and their cures. United Kingdom: Oxford University Press; 2010.

5. Imbens GW. Causality in econometrics: choice vs chance. Econometrica. 2022;90(6):2541–66.

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