Modeling Heterogeneous Peer Assortment Effects using Latent Class Pseudo-Maximum Likelihood Exponential Random Graph Models Public Deposited

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Last Modified
  • March 19, 2019
Creator
  • Henry, Teague
    • Affiliation: College of Arts and Sciences, Department of Psychology and Neuroscience
Abstract
  • This thesis develops a class of models for inference on networks called Sender/Receiver Latent Class Exponential Random Graph Models (SRLCERGMs). This class of models extends the existing Exponential Random Graph Modeling framework to allow analysts to model unobserved heterogeneity in the effects of nodal covariates and network features. Simulations across a variety of conditions are presented to evaluate the performance of this technique, and an empirical example regarding substance use among adolescents is also presented. Implications for the analysis of social networks in psychological science are discussed.
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Rights statement
  • In Copyright
Advisor
  • Mucha, Peter
  • Gates, Kathleen
  • Bauer, Daniel
Degree
  • Master of Arts
Degree granting institution
  • University of North Carolina at Chapel Hill Graduate School
Graduation year
  • 2015
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Place of publication
  • Chapel Hill, NC
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