Abstract Details
Activity Number:
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668
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Type:
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Topic Contributed
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Date/Time:
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Thursday, August 8, 2013 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Epidemiology
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Abstract - #310442 |
Title:
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Testing of and Modeling Dependencies Between a Network and Nodal Attributes
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Author(s):
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Bailey Fosdick*+ and Peter David Hoff
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Companies:
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University of Washington and University of Washington
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Keywords:
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network ;
nodal attribute ;
dependencies ;
covariance ;
latent variable
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Abstract:
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Social network analysis is often focused on characterizing the dependencies between network relations and node-level attributes. Potential relationships are typically explored by modeling the network as a function of the nodal attributes or by modeling the attributes as a function of the network. These methods require specification of the exact nature of the association between the network and attributes, reduce the network data to a small number of summary statistics, and are unable provide predictions simultaneously for missing attribute and network information. In this talk we introduce methodology that addresses these shortcomings; we propose a formal testing procedure for determining if a relationship between the network and attributes exists and a joint model for the network and attributes that can capture a variety of dependence patterns. This model is an extension of the latent variable network models presented in Hoff (2005) and Hoff (2009).
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Authors who are presenting talks have a * after their name.
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