A theoretical and empirical comparison of the temporal exponential random graph model and the stochastic actor-oriented model

The temporal exponential random graph model (TERGM) and the stochastic actor-oriented model (SAOM, e.g., SIENA) are popular models for longitudinal network analysis. We compare these models theoretically, via simulation, and through a real-data example in order to assess their relative strengths and...

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Veröffentlicht in:Network science (Cambridge University Press) 2019-03, Vol.7 (1), p.20-51
Hauptverfasser: Leifeld, Philip, Cranmer, Skyler J.
Format: Artikel
Sprache:eng
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Zusammenfassung:The temporal exponential random graph model (TERGM) and the stochastic actor-oriented model (SAOM, e.g., SIENA) are popular models for longitudinal network analysis. We compare these models theoretically, via simulation, and through a real-data example in order to assess their relative strengths and weaknesses. Though we do not aim to make a general claim about either being superior to the other across all specifications, we highlight several theoretical differences the analyst might consider and find that with some specifications, the two models behave very similarly, while each model out-predicts the other one the more the specific assumptions of the respective model are met.
ISSN:2050-1242
2050-1250
DOI:10.1017/nws.2018.26