Debate continues over whether job instability is rising in the United States, with data and measurement complicating the search for definitive answers. In this paper we compare two cohorts of young white men from the National Longitudinal Surveys (NLS), construct a rigorous measure of job...

We describe some of the capabilities of the ergm package and the statistical theory underlying it. This package contains tools for accomplishing three important, and inter-related, tasks involving exponential-family random graph models (ERGMs): estimation, simulation, and goodness of fit. More...

Exponential-family random graph models (ERGMs) represent the processes that govern the formation of links in networks through the terms selected by the user. The terms specify network statistics that are sufficient to represent the probability distribution over the space of networks of that...

The statnet suite of R packages contains a wide range of functionality for the statistical analysis of social networks, including the implementation of exponential-family random graph (ERG) models. In this paper we illustrate some of the functionality of statnet through a tutorial analysis of a...

statnet is a suite of software packages for statistical network analysis. The packages implement recent advances in network modeling based on exponential-family random graph models (ERGM). The components of the package provide a comprehensive framework for ERGM-based network modeling, including...

Work with longitudinal network survey data and the dynamic network outputs of the statnet ERGMs has demonstrated the need for consistent frameworks and data structures for expressing, storing, and manipulating information about networks that change in time. Motivated by our requirements for...

In this paper we explore patterns of economic transfers between adults within household and family networks in a village in Malawi’s Rumphi district, using data from the 2006 round of the Malawi Longitudinal Study of Families and Health. We fit Exponential-family Random Graph Models...

In non-experimental research, data on the same population process may be collected simultaneously by more than one instrument. For example, in the present application, two sample surveys and a population birth registration system all collect observations on first births by age and year, while...

Previous studies have demonstrated both large efficiency gains and reductions in bias by incorporating population information in regression estimation with sample survey data. These studies, however, assume the population values are exact. This assumption is relaxed here through a Bayesian...

The ability to simulate graphs with given properties is important for the analysis of social networks. Sequential importance sampling has been shown to be particularly effective in estimating the number of graphs adhering to fixed marginals and in estimating the null distribution of graph...