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Mediation and Moderation in Statistical Network Models

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  • Duxbury, Scott W

Abstract

Statistical network methods have grown increasingly popular in the social sciences. However, like other nonlinear probability models, statistical network model parameters can only be identified to a scale and cannot be compared between groups or models fit to the same network. This study addresses these issues by developing methods for mediation and moderation analyses in exponential random graph models (ERGM). It first discusses ERGM as an autologistic regression to illustrate that ERGM estimates can be affected by unobserved heterogeneity. Second, it develops methods for mediation analysis for both discrete and continuous mediators. Third, it provides recommendations and methods for interpreting interactions in ERGM. Finally, it considers scenarios where interactions are implicated in mediation analysis. The methodological discussion is accompanied with empirical applications and extensions to other classes of statistical network models are discussed.

Suggested Citation

  • Duxbury, Scott W, 2019. "Mediation and Moderation in Statistical Network Models," SocArXiv 9bs4u, Center for Open Science.
    • Handle: RePEc:osf:socarx:9bs4u
    DOI: 10.31219/osf.io/9bs4u
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