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Model selection in random effects models for directed graphs using approximated Bayes factors

Abstract:
With the development of an MCMC algorithm, Bayesian model selection for the p2 model for directed graphs has become possible. This paper presents an empirical exploration in using approximate Bayes factors for model selection. For a social network of Dutch secondary school pupils from different ethnic backgrounds it is investigated whether pupils report that they receive more emotional support from within their own ethnic group. Approximated Bayes factors seem to work, but considerable margins of error have to be reckoned with. © VVS, 2005.
Publication status:
Published

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Authors


Zijlstra, BJH More by this author
van Duijn, MAJ More by this author
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Institution:
University of Oxford
Department:
Oxford, MPLS, Statistics
Journal:
STATISTICA NEERLANDICA
Volume:
59
Issue:
1
Pages:
107-118
Publication date:
2005-02-05
DOI:
EISSN:
1467-9574
ISSN:
0039-0402
URN:
uuid:b5610067-8c49-45e5-9a7e-08820930132b
Source identifiers:
97779
Local pid:
pubs:97779

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