International Statistical Review
- Internat. Statist. Rev.
- Volume 72, Number 3 (2004), 285-305.
Causality: a Statistical View
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.
Internat. Statist. Rev., Volume 72, Number 3 (2004), 285-305.
First available in Project Euclid: 8 December 2004
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Chain block graph Counterfactual Explanation Instrumental variable Interaction Markov graph Observational study Overview Regression analysis Surrogate variable Unit-treatment additivity Unobserved confounder
Cox, D.R.; Wermuth, Nanny. Causality: a Statistical View. Internat. Statist. Rev. 72 (2004), no. 3, 285--305. https://projecteuclid.org/euclid.isr/1102516472