Uncertainty in Artificial Intelligence
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Causal Inference in the Presence of Latent Variables and Selection Bias
Peter Spirtes, Christopher Meek, Thomas Richardson
Abstract:
We show that there is a general, informative and reliable procedure for discovering causal relations when, for all the investigator knows, both latent variables and selection bias may be at work. Given information about conditional independence and dependence relations between measured variables, even when latent variables and selection bias may be present, there are sufficient conditions for reliably concluding that there is a causal path from one variable to another, and sufficient conditions for reliably concluding when no such causal path exists.
Keywords: Causal inference, selection bias, latent variables, FCI.
Pages: 499-506
PS Link:
PDF Link: /papers/95/p499-spirtes.pdf
BibTex:
@INPROCEEDINGS{Spirtes95,
AUTHOR = "Peter Spirtes and Christopher Meek and Thomas Richardson",
TITLE = "Causal Inference in the Presence of Latent Variables and Selection Bias",
BOOKTITLE = "Proceedings of the Eleventh Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-95)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1995",
PAGES = "499--506"
}


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