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Bayesian analysis of social influence

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  • Johan Koskinen
  • Galina Daraganova

Abstract

The network influence model is a model for binary outcome variables that accounts for dependencies between outcomes for units that are relationally tied. The basic influence model was previously extended to afford a suite of new dependence assumptions and because of its relation to traditional Markov random field models it is often referred to as the auto logistic actor‐attribute model (ALAAM). We extend on current approaches for fitting ALAAMs by presenting a comprehensive Bayesian inference scheme that supports testing of dependencies across subsets of data and the presence of missing data. We illustrate different aspects of the procedures through three empirical examples: masculinity attitudes in an all‐male Australian school class, educational progression in Swedish schools, and unemployment among adults in a community sample in Australia.

Suggested Citation

  • Johan Koskinen & Galina Daraganova, 2022. "Bayesian analysis of social influence," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1855-1881, October.
    • Handle: RePEc:bla:jorssa:v:185:y:2022:i:4:p:1855-1881
    DOI: 10.1111/rssa.12844
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    Cited by:

    1. Alex Stivala & Peng Wang & Alessandro Lomi, 2024. "ALAAMEE: Open-source software for fitting autologistic actor attribute models," PLOS Complex Systems, Public Library of Science, vol. 1(4), pages 1-32, December.
    2. Hashimi, Sadaf & Ouellet, Marie, 2025. "Invite only: The prevalence of subgroups within a police department," Journal of Criminal Justice, Elsevier, vol. 96(C).

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