A Theoretical and Empirical Comparison of the Temporal Exponential Random Graph Model and the Stochastic Actor-Oriented Model

Leifeld, Philip; Cranmer, Skyler J.

A Theoretical and Empirical Comparison of the Temporal Exponential Random Graph Model and the Stochastic Actor-Oriented Model

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Date

2015

Publication type

Preprint

Abstract

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 one cannot make a general claim about either being superior to the other across specifications, we find that the more restrictive assumptions of the SAOM must be met exactly in order for it to perform comparably to the TERGM. Otherwise, we find that the TERGM outperforms the SAOM in out-of-sample prediction by substantial margins.

Subject (DDC)

510 Mathematics

Cite This

ISO 690

LEIFELD, Philip, Skyler J. CRANMER, 2015. A Theoretical and Empirical Comparison of the Temporal Exponential Random Graph Model and the Stochastic Actor-Oriented Model

BibTex

@unpublished{Leifeld2015Theor-31942,
  year={2015},
  title={A Theoretical and Empirical Comparison of the Temporal Exponential Random Graph Model and the Stochastic Actor-Oriented Model},
  author={Leifeld, Philip and Cranmer, Skyler J.}
}

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