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dc.contributor.authorGallupe, Owen
dc.contributor.authorMcLevey, John
dc.contributor.authorBrown, Sarah 15:32:41 (GMT) 15:32:41 (GMT)
dc.descriptionThis is a post-peer-review, pre-copyedit version of an article published in the Journal of Quantitative Criminology. The final authenticated version is available online at:
dc.description.abstractObjectives 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. Methods 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. Results 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. Conclusions People are both influenced by the offending of their peers and select into friendships based on similarity in offending.en
dc.subjectstochastic actor-oriented modelsen
dc.titleSelection and Influence: A Meta-Analysis of the Association Between Peer and Personal Offendingen
dcterms.bibliographicCitationGallupe, Owen, John McLevey, and Sarah Brown. ‘Selection and Influence: A Meta-Analysis of the Association Between Peer and Personal Offending’. Journal of Quantitative Criminology 35, no. 2 (1 June 2019): 313–35.
uws.contributor.affiliation1Faculty of Artsen
uws.contributor.affiliation1Faculty of Environmenten
uws.contributor.affiliation2Knowledge Integrationen
uws.contributor.affiliation2Sociology and Legal Studiesen
uws.contributor.affiliation2Waterloo Libraryen

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