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The New England Journal of Statistics in Data Science


Bayesian Estimation of Contagion Effect: An Application of Friendship Networks and Alcohol Behavior
Pub. online: 9 March 2026      Type: Methodology Article      Open accessOpen Access
Area: Statistical Methodology
Accepted
26 September 2025
Published
9 March 2026

Abstract

Social networks primarily focus on the phenomenon of the contagion effect when examining behavior patterns within specific social groups. However, the impact of peer effects is characterized by the tendency to imitate the behaviors of friends and the selection process, where individuals tend to affiliate with others sharing similar traits, significantly contributing to shaping social behaviors that are frequently interconnecting. This article presents a Bayesian approach that uses latent-space estimation methods to detect and examine contagion effects, considering the impact of social selection. The research provides a methodological explanation, followed by a sequence of simulation trials designed to explore operational functionalities and possible real-world applications. To illustrate the potential correlation between changes in alcohol use and the influence of social networks, this study concludes by presenting an example of adolescent drinking behavior.

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Copyright
© 2026 New England Statistical Society
Open access article under the CC BY license.

Keywords
Bayes analysis Contagion effect Latent space Social selection Friendship network

Funding
Victor Lachos acknowledges partial financial support from the Research Excellence Program (REP) at UConn-OVPR.

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