, Volume 66, Issue 2, pp 161–189

Network models for social influence processes


DOI: 10.1007/BF02294834

Cite this article as:
Robins, G., Pattison, P. & Elliott, P. Psychometrika (2001) 66: 161. doi:10.1007/BF02294834


This paper generalizes thep* class of models for social network data to predict individual-level attributes from network ties. Thep* model for social networks permits the modeling of social relationships in terms of particular local relational or network configurations. In this paper we present methods for modeling attribute measures in terms of network ties, and so constructp* models for the patterns of social influence within a network. Attribute variables are included in a directed dependence graph and the Hammersley-Clifford theorem is employed to derive probability models whose parameters can be estimated using maximum pseudo-likelihood. The models are compared to existing network effects models. They can be interpreted in terms of public or private social influence phenomena within groups. The models are illustrated by an empirical example involving a training course, with trainees' reactions to aspects of the course found to relate to those of their network partners.

Key words

social networks social influence p* models network effects models attitudes graphical models 

Copyright information

© The Psychometric Society 2001

Authors and Affiliations

  • Garry Robins
    • 2
  • Philippa Pattison
    • 2
  • Peter Elliott
    • 1
  1. 1.Swinburne University of TechnologyAustralia
  2. 2.School of Behavioural Science, Department of PsychologyThe University of MelbourneMelbourneAustralia

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