Using descendants as instrumental variables for the identification of direct causal effects in linear SEMs

Journal of Machine Learning Research

Volumn 9, Issue , 2010, Pages 73-80

  Chan, Hei ^a   Kuroki, Manabu ^b  

^a INSTITUTE OF STATISTICAL MATHEMATICS   (Japan)

^b OSAKA UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

GRAPHICAL CRITERIA; GRAPHICAL MODEL; IDENTIFIABILITY; INSTRUMENTAL VARIABLES; STRUCTURAL EQUATION MODELS; TOTAL EFFECT;

SOFTWARE ENGINEERING;

ARTIFICIAL INTELLIGENCE;

EID: 84862290109     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Conference Paper

References (17)

1. Kenneth A. Bollen. Structural Equations with Latent Variables. John Wiley, 1989.
2. Roger J. Bowden and Darrell A. Turkington. Instrumental Variables. Cambridge University Press, 1984.
3. Carlos Brito and Judea Pearl. A graphical criterion for the identification of causal effects in linear models. In Proceedings of the Eighteenth National Conference on Artificial Intelligence (AAAI), pages 533-538. AAAI Press, 2002a.
4. Carlos Brito and Judea Pearl. A new identification condition for recursive models with correlated errors. Structural Equation Modeling, 9(4):459-474, 2002b.
5. Carlos Brito and Judea Pearl. Generalized instrumental variables. In Proceedings of the Eighteenth Conference on Uncertainty in Artificial Intelligence (UAI), pages 85-93. Morgan Kaufmann Publishers, 2002c.
6. Carlos Brito and Judea Pearl. Graphical condition for identification in recursive SEM. In Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (UAI), pages 47-54. AUAI Press, 2006.
7. Zhihong Cai and Manabu Kuroki. On identifying total effects in the presence of latent variables and selection bias. In Proceedings of the Twenty-Third Conference on Uncertainty in Artificial Intelligence (UAI), pages 62-69. AUAI Press, 2008.
8. Otis D. Duncan. Introduction to Structural Equation Models. Academic Press, 1975.
9. Franklin M. Fisher. The Identification Problem in Econometrics. McGraw-Hill, 1966.
10. Judea Pearl. Robustness of causal claims. In Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence (UAI), pages 446-453. AUAI Press, 2004.
11. Judea Pearl. Causality: Models, Reasoning, and Inference. Cambridge University Press, 2nd edition, 2009. 1st edition, 2000.
12. Peter Spirtes, Clark Glymour, and Richard Scheines. Causation, Prediction, and Search. MIT Press, 2000.
13. Jin Tian. Identifying linear causal effects. In Proceedings of the Eighteenth National Conference on Artificial Intelligence (AAAI), pages 104-111. AAAI Press, 2004.
14. Jin Tian. Identifying direct causal effects in linear models. In Proceedings of the Nineteenth National Conference on Artificial Intelligence (AAAI), pages 346-353. AAAI Press, 2005.
15. Jin Tian. On the identification of a class of linear models. In Proceedings of the Twenty-Second National Conference on Artificial Intelligence (AAAI), pages 1284-1289. AAAI Press, 2007a.
16. Jin Tian. A criterion for parameter identification in structural equation models. In Proceedings of the Twenty-Third Conference on Uncertainty in Artificial Intelligence (UAI), pages 392-399. AUAI Press, 2007b.
17. Sewall Wright. The method of path coefficients. Annals of Mathematical Science, 5(3):161-215, 1934.