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Abstract Details
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Activity Number:
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211
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Type:
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Invited
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Date/Time:
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Monday, July 30, 2012 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #303913 |
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Title:
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Causal Models Associated with Acyclic Directed Mixed Graphs
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Author(s):
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Thomas Richardson*+ and James Robins and Ilya Shipster and Robin J. Evans
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Companies:
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University of Washington and Harvard University and Harvard School of Public Health and Cambridge University
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Address:
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, , ,
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Keywords:
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Abstract:
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Acyclic directed mixed graphs may be used to represent causal directed acyclic graph (DAG) models in which some variables are unmeasured (latent). In this talk we present a parametrization of the observed distribution in the multivariate binary case. The resulting model satisfies Markov constraints, and so-called Verma constraints. The parametrization leads to efficient algorithms for computing intervention distributions, as well as allowing scoring-based model search.
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Authors who are presenting talks have a * after their name.
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