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Abstract Details

Activity Number: 211
Type: Invited
Date/Time: Monday, July 30, 2012 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #303913
Title: Causal Models Associated with Acyclic Directed Mixed Graphs
Author(s): Thomas Richardson*+ and James Robins and Ilya Shipster and Robin J. Evans
Companies: University of Washington and Harvard University and Harvard School of Public Health and Cambridge University
Address: , , ,

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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