Bayesian Analysis of Social Influence
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 un-employment among adults in a community sample in Australia.
Cite
@article{arxiv.2006.16464,
title = {Bayesian Analysis of Social Influence},
author = {Johan Koskinen and Galina Daraganova},
journal= {arXiv preprint arXiv:2006.16464},
year = {2022}
}