Direct and Indirect Effects

Abstract

The direct effect of one event on another can be defined and measured by holding constant all intermediate variables between the two. Indirect effects present conceptual and practical difficulties (in nonlinear models), because they cannot be isolated by holding certain variables constant. This paper presents a new way of defining the effect transmitted through a restricted set of paths, without controlling variables on the remaining paths. This permits the assessment of a more natural type of direct and indirect effects, one that is applicable in both linear and nonlinear models and that has broader policy-related interpretations. The paper establishes conditions under which such assessments can be estimated consistently from experimental and nonexperimental data, and thus extends path-analytic techniques to nonlinear and nonparametric models.

Cite

Text

Pearl. "Direct and Indirect Effects." Conference on Uncertainty in Artificial Intelligence, 2001. doi:10.1145/3501714.3501736

Markdown

[Pearl. "Direct and Indirect Effects." Conference on Uncertainty in Artificial Intelligence, 2001.](https://mlanthology.org/uai/2001/pearl2001uai-direct/) doi:10.1145/3501714.3501736

BibTeX

@inproceedings{pearl2001uai-direct,
  title     = {{Direct and Indirect Effects}},
  author    = {Pearl, Judea},
  booktitle = {Conference on Uncertainty in Artificial Intelligence},
  year      = {2001},
  pages     = {411-420},
  doi       = {10.1145/3501714.3501736},
  url       = {https://mlanthology.org/uai/2001/pearl2001uai-direct/}
}