Factorization of the Partial Covariance in Singly-Connected Path Diagrams
Abstract
We extend path analysis by showing that, for a singly-connected path diagram, the partial covariance of two random variables factorizes over the nodes and edges in the path between the variables. This result allows us to determine the contribution of each node and edge to the partial covariance. It also allows us to show that Simpson’s paradox cannot occur in singly-connected path diagrams.
Cite
Text
Peña. "Factorization of the Partial Covariance in Singly-Connected Path Diagrams." Proceedings of the Second Conference on Causal Learning and Reasoning, 2023.Markdown
[Peña. "Factorization of the Partial Covariance in Singly-Connected Path Diagrams." Proceedings of the Second Conference on Causal Learning and Reasoning, 2023.](https://mlanthology.org/clear/2023/pena2023clear-factorization/)BibTeX
@inproceedings{pena2023clear-factorization,
title = {{Factorization of the Partial Covariance in Singly-Connected Path Diagrams}},
author = {Peña, Jose},
booktitle = {Proceedings of the Second Conference on Causal Learning and Reasoning},
year = {2023},
pages = {814-849},
volume = {213},
url = {https://mlanthology.org/clear/2023/pena2023clear-factorization/}
}