International Statistical Review

Causality: a Statistical View

D.R. Cox and Nanny Wermuth

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Abstract

Statistical aspects of causality are reviewed in simple form and the impact of recent work discussed. Three distinct notions of causality are set out and implications for densities and for linear dependencies explained. The importance of appreciating the possibility of effect modifiers is stressed, be they intermediate variables, background variables or unobserved confounders. In many contexts the issue of unobserved confounders is salient. The difficulties of interpretation when there are joint effects are discussed and possible modifications of analysis explained. The dangers of uncritical conditioning and marginalization over intermediate response variables are set out and some of the problems of generalizing conclusions to populations and individuals explained. In general terms the importance of search for possibly causal variables is stressed but the need for caution is emphasized.

Article information

Source
Internat. Statist. Rev., Volume 72, Number 3 (2004), 285-305.

Dates
First available in Project Euclid: 8 December 2004

Permanent link to this document
https://projecteuclid.org/euclid.isr/1102516472

Mathematical Reviews number (MathSciNet)
MR2090633

Keywords
Chain block graph Counterfactual Explanation Instrumental variable Interaction Markov graph Observational study Overview Regression analysis Surrogate variable Unit-treatment additivity Unobserved confounder

Citation

Cox, D.R.; Wermuth, Nanny. Causality: a Statistical View. Internat. Statist. Rev. 72 (2004), no. 3, 285--305. https://projecteuclid.org/euclid.isr/1102516472


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