Exact variance formula for the estimated mean outcome with external intervention based on the front-door criterion in Gaussian linear structural equation models

DOI10.1016/j.jmva.2021.104766zbMath1479.62039OpenAlexW3162862441MaRDI QIDQ2048113

Manabu Kuroki, Hisayoshi Nanmo

Publication date: 5 August 2021

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2021.104766

zbMATH Keywords

identificationcausal effecttotal effectpath diagramstructural causal modelfront-door criterion

Mathematics Subject Classification ID

Probabilistic graphical models (62H22) Causal inference from observational studies (62D20)

Cites Work

• Identification of causal effects in linear models: beyond instrumental variables
• Covariate selection for identifying the effects of a particular type of conditional plan using causal networks
• Covariate selection for identifying the causal effects of stochastic interventions using causal networks
• Variance formulas for estimated mean response and predicted response with external intervention based on the back-door criterion in linear structural equation models
• A generalized back-door criterion
• On the Estimation Accuracy of Causal Effects using Supplementary Variables
• Measurement bias and effect restoration in causal inference
• Covariate Selection for Estimating the Causal Effect of Control Plans by Using Causal Diagrams
• Optimizing a control plan using a structural equation model with an application to statistical process analysis
• Observational studies.
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