Selection and Influence: A Meta-Analysis of the Association Between Peer and Personal Offending
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Whether people are affected by the criminal behavior of peers (the “influence” perspective) or simply prefer to associate with others who are similar in their offending (the “selection” perspective) is a long-standing criminological debate. The relatively recent development of stochastic actor-oriented models (SAOMs—also called SIENA models) for longitudinal social network data has allowed for the examination of selection and influence effects in more comprehensive ways than was previously possible. This article reports the results of a systematic review and meta-analysis of studies that use SAOMs to test for peer selection and influence effects.
A systematic review and 3-level random effects meta-analysis of studies that have used SAOMs to test selection and influence dynamics for offending behavior.
There is support for both influence (mean log odds ratio = 1.23, p < 0.01, 21 effects, pooled n = 21,193) and selection dynamics (mean log odds ratio = 0.31, p < 0.01, 28 effects, pooled n = 21,269). Type of behavior, country, and the year of the first wave of data collection are found to moderate the influence effect; no significant moderation effects are found for peer selection on offending.
People are both influenced by the offending of their peers and select into friendships based on similarity in offending.
KeywordsSelection Influence Crime Meta-analysis Stochastic actor-oriented models
The authors would like to thank Nate Doogan for his valuable comments on an earlier version of this article.
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