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Identifying direct and indirect effects in a non‐counterfactual framework
Author(s) -
Geneletti Sara
Publication year - 2007
Publication title -
journal of the royal statistical society: series b (statistical methodology)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.523
H-Index - 137
eISSN - 1467-9868
pISSN - 1369-7412
DOI - 10.1111/j.1467-9868.2007.00584.x
Subject(s) - counterfactual thinking , indirect effect , variable (mathematics) , causal inference , channelling , inference , causal model , econometrics , computer science , psychology , social psychology , mathematics , artificial intelligence , chemistry , statistics , political science , law , mathematical analysis , ion , organic chemistry
Summary. Identifying direct and indirect effects is a common problem in the social science and medical literature and can be described as follows. A treatment is administered and a response is recorded. However, another variable mediates the effect of the treatment on the response, in some way channelling a part of the treatment effect. The question is how to extricate the direct and channelled (indirect) effects from one another when it is not possible to intervene on the mediating variable. The aim of the paper is to tackle this problem by using a model for direct and indirect effects based on the decision theoretic framework for causal inference.