This article discusses the stochastic actor-oriented model for analyzing panel data of
networks. The model is defined as a continuous-time Markov chain, observed at two or more …

Political science is fascinated with networks. This fascination builds on networks' descriptive
appeal, and descriptions of networks play a prominent role in recent forays into network …

The most commonly used statistical models of civil war onset fail to correctly predict most
occurrences of this rare event in out-of-sample data. Statistical methods for the analysis of …

The empirical literature that examines cross-national patterns of state repression seeks to
discover a set of political, economic, and social conditions that are consistently associated …

International relations research has regarded networks as a particular mode of organization,
distinguished from markets or state hierarchies. In contrast, network analysis permits the …

Spatial Regression Models illustrates the use of spatial analysis in the social sciences within
a regression framework and is accessible to readers with no prior background in spatial …

Methods for descriptive network analysis have reached statistical maturity and general
acceptance across the social sciences in recent years. However, methods for statistical …

Two studies question whether economic interdependence promotes peace, arguing that
previous research has not adequately considered the endogeneity of trade. Using …

Exponential-family random graph models (ERGMs) provide a principled and flexible way to
model and simulate features common in social networks, such as propensities for …

We present a selective review of statistical modeling of dynamic networks. We focus on
models with latent variables, specifically, the latent space models and the latent class …