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 interrelated, tasks involving exponential-family random graph models (ERGMs): estimation, simulation, and goodness of fit. More precisely, ergm has the capability of approximating a maximum likelihood estimator for an ERGM given a network data set; simulating new network data sets from a fitted ERGM using Markov chain Monte Carlo; and assessing how well a fitted ERGM does at capturing characteristics of a particular network data set.

Abstractstatnet 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 tools for model estimation, model evaluation, model-based network simulation, and network visualization. This broad functionality is powered by a central Markov chain Monte Carlo (MCMC) algorithm. The coding is optimized for speed and robustness.

Concurrent partnerships may be as important as multiple partners or cofactor infections in amplifying the spread of HIV. The public health implications are that data must be collected properly to measure the levels of concurrency in a population, and that messages promoting one partner at a time are as important as messages promoting fewer partners.

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Median income in the United States has fallen and the distribution of income has grown markedly more unequal over the past three decades, reversing a general pattern of earnings growth and equalization dating back to 1929. Median trends were not the same for all groups-women's earnings generally increased-but the growth in earnings inequality has been experienced by all groups. Even white men employed full-time, year-round-traditionally the most privileged and secure group-could not escape wage stagnation and polarization. These patterns suggest research questions that go beyond conventional sociological interest in racial and gender wage gaps, refocusing attention on more general changes in labor market dynamics. The debates over the origins of the rise in US inequality cover a wide range of issues that can be roughly grouped into four categories: the changing demographics of the labor force, the impact of economic restructuring, the role of political context and institutions, and the dynamics of globalization. We review the empirical literature here, and challenge the field of sociology to reconstruct its research agenda on stratification and inequality.

In this article, we use newly developed statistical methods to examine the generative processes that give rise to widespread patterns in friendship networks. The methods incorporate both traditional demographic measures on individuals (age, sex, and race) and network measures for structural processes operating on individual, dyadic, and triadic levels. We apply the methods to adolescent friendship networks in 59 U.S. schools from the National Longitudinal Survey of Adolescent Health (Add Health). We model friendship formation as a selection process constrained by individuals' sociality (propensity to make friends), selective mixing in dyads (friendships within race, grade, or sex categories are differentially likely relative to cross-category friendships), and closure in triads (a friend's friends are more likely to become friends), given local population composition. Blacks are generally the most cohesive racial category, although when whites are in the minority, they display stronger selective mixing than do blacks when blacks are in the minority. Hispanics exhibit disassortative selective mixing under certain circumstances; in other cases, they exhibit assortative mixing but lack the higher-order cohesion common in other groups. Grade levels are always highly cohesive, while females form triangles more than males. We conclude with a discussion of how network analysis may contribute to our understanding of sociodemographic structure and the processes that create it.

Concurrent sexual partnerships may help to explain the disproportionately high prevalence of HIV and other sexually transmitted infections among African Americans. The persistence of such disparities would also require strong assortative mixing by race. We examined descriptive evidence from 4 nationally representative US surveys and found consistent support for both elements of this hypothesis. Using a data-driven network simulation model, we found that the levels of concurrency and assortative mixing observed produced a 2.6-fold racial disparity in the epidemic potential among young African American adults.

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