network-modeling

Estimating Within-School Contact Networks To Understand Influenza Transmission

Many epidemic models approximate social contact behavior by assuming random mixing within mixing groups (e.g., homes, schools and workplaces). The effect of more realistic social network structure on estimates of epidemic parameters is an open area …

Improving simulation-based algorithms for fitting ERGMs

Markov chain Monte Carlo methods can be used to approximate the intractable normalizing constants that arise in likelihood calculations for many exponential-family random graph models for networks. However, in practice, the resulting approximations …

On the Concept of Snowball Sampling

A phenomenon in the sociology of science is that multidisciplinary fields tend to produce a plethora of inconsistent terminology. Often the meaning of a term evolves over time, or different terms are used for the same concept. More confusing is the …

Estimating Within-Household Contact Networks from Egocentric Data

Acute respiratory diseases are transmitted over networks of social contacts. Large-scale simulation models are used to predict epidemic dynamics and evaluate the impact of various interventions, but the contact behavior in these models is based on …

Adjusting for network size and composition effects in exponential-family random graph models

Exponential-family random graph models (ERGMs) provide a principled way to model and simulate features common in human social networks, such as propensities for homophily and friend-of-a-friend triad closure. We show that, without adjustment, ERGMs …

A Description of Within-family Resource Exchange Networks in a Malawian Village

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 …

Respondent-Driven Sampling: An Assessment of Current Methodology

Respondent-driven sampling (RDS) employs a variant of a link-tracing network sampling strategy to collect data from hard-to-reach populations. By tracing the links in the underlying social network, the process exploits the social structure to expand …

A Framework for the Comparison of Maximum Pseudo Likelihood and Maximum Likelihood Estimation of Exponential Family Random Graph Models

The statistical modeling of social network data is difficult due to the complex dependence structure of the tie variables. Statistical exponential families of distributions provide a flexible way to model such dependence. They enable the statistical …

A curved exponential family model for complex networks

Networks are being increasingly used to represent relational data. As the patterns of relations tends to be complex, many probabilistic models have been proposed to capture the structural properties of the process that generated the networks. Two …

A statnet Tutorial

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 …