136 citations · 277 across the 10 of their papers we have counts for
5 papers · 1 filter
Inferring Influence Networks from Longitudinal Bipartite Relational Data
Frank W. Marrs, Benjamin W. Campbell, Bailey K. Fosdick +2
Longitudinal bipartite relational data characterize the evolution of relations between pairs of actors, where actors are of two distinct types and relations exist only between disp…
What can we Learn from Predictive Modeling?
Skyler J. Cranmer, Bruce A. Desmarais
The large majority of inferences drawn in empirical political research follow from model-based associations (e.g. regression). Here, we articulate the benefits of predictive modeli…
A Critique of Dyadic Design
Skyler J. Cranmer, Bruce A. Desmarais
Dyadic research designs concern data that comprises interactions among actors. Dyadic approaches unambiguously constitute the most frequent designs employed in the empirical study…
A Theoretical and Empirical Comparison of the Temporal Exponential Random Graph Model and the Stochastic Actor-Oriented Model
Philip Leifeld, Skyler J. Cranmer
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 the…
Stochastic Weighted Graphs: Flexible Model Specification and Simulation
James D. Wilson, Matthew J. Denny, Shankar Bhamidi +2
In most domains of network analysis researchers consider networks that arise in nature with weighted edges. Such networks are routinely dichotomized in the interest of using availa…