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ERIC Number: EJ1136517
Record Type: Journal
Publication Date: 2015-May
Pages: 50
Abstractor: As Provided
ISSN: ISSN-0049-1241
Representing Micro-Macro Linkages by Actor-Based Dynamic Network Models
Snijders, Tom A. B.; Steglich, Christian E. G.
Sociological Methods & Research, v44 n2 p222-271 May 2015
Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of generalized linear statistical models they aim to be realistic detailed representations of network dynamics in empirical data sets. Statistical parallels to micro--macro considerations can be found in the estimation of parameters determining local actor behavior from empirical data, and the assessment of goodness of fit from the correspondence with network-level descriptives. This article studies several network-level consequences of dynamic actor-based models applied to represent cross-sectional network data. Two examples illustrate how network-level characteristics can be obtained as emergent features implied by microspecifications of actor-based models.
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Publication Type: Journal Articles; Reports - Research
Education Level: Secondary Education
Audience: N/A
Language: English
Sponsor: National Institutes of Health (DHHS)
Authoring Institution: N/A
Identifiers - Location: United Kingdom (Glasgow)
Grant or Contract Numbers: 1R01HD05288701A2