Research on the Graphical Model Structure Characteristic of Strong Exogeneity Based on Twin Network Method and Its Application in Causal Inference

Rui Luo, Lijia Sun, Yin Kuang, Ping Deng and Mengna Lu
Additional contact information
Rui Luo: Key Lab of Interior Layout optimization and Security, Chengdu Normal University, Chengdu 611130, China
Lijia Sun: School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
Yin Kuang: Key Lab of Interior Layout optimization and Security, Chengdu Normal University, Chengdu 611130, China
Ping Deng: Key Lab of Information Coding and Transmission, Southwest Jiaotong University, Chengdu 611756, China
Mengna Lu: School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu 611731, China

Mathematics, 2022, vol. 10, issue 6, 1-13

Abstract: Strong exogeneity is an important assumption in the study of causal inference, but it is difficult to identify according to its definition. The twin network method provides a graphical model tool for analyzing the variable relationship, involving the actual world and the hypothetical world, which facilitates the investigating of strong exogeneity. In this paper, the graphical model structure characteristic of strong exogeneity is investigated based on the twin network method. Compared with other derivation methods of graphical diagnosis, the method based on the twin network is more concise, clearer, and easier to understand. Under the condition of strong exogeneity, it is easy to estimate the probability of causation based on observational data. As an example, the application of graphical model structure characteristic of strong exogeneity in causal inference in the context of lung cancer simple sets (LUCAS) is illustrated.

Keywords: causal effect; exogeneity; graphical model; observational data; probability of causation; twin network (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/10/6/957/pdf (application/pdf)
https://www.mdpi.com/2227-7390/10/6/957/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:10:y:2022:i:6:p:957-:d:773206

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().