Structural equation modeling for causal effect estimation with machine learning

Causal inference is a crucial framework in a variety of fields, such as economics, healthcare, and social science. In this context, data-driven machine learning models have become more popular for estimating the effects of treatments. One fundamental technique for causal inference is structural equa...

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Veröffentlicht in:	Journal of computational and applied mathematics Jg. 475; S. 117020
Hauptverfasser:	Ahmad, Sohail, Shah, Kamal, Debbouche, Amar
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 15.03.2026
Schlagworte:	Backdoor criterion Causal inference Confounding variables Machine learning Piecewise SEM Structural causal model Causal inference Confounding variables Piecewise SEM Structural causal model Backdoor criterion Machine learning
ISSN:	0377-0427
Online-Zugang:	Volltext
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