Uncertainty in Artificial Intelligence
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On the Testability of Causal Models with Latent and Instrumental Variables
Judea Pearl
Certain causal models involving unmeasured variables induce no independence constraints among the observed variables but imply, nevertheless, inequality contraints on the observed distribution. This paper derives a general formula for such instrumental variables, that is, exogenous variables that directly affect some variables but not all. With the help of this formula, it is possible to test whether a model involving instrumental variables may account for the data, or, conversely, whether a given variables can be deemed instrumental.
Keywords: Causal modeling, insrumental variables, structural models, graphical models.
Pages: 435-443
PS Link:
PDF Link: /papers/95/p435-pearl.pdf
AUTHOR = "Judea Pearl ",
TITLE = "On the Testability of Causal Models with Latent and Instrumental Variables",
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 = "435--443"

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