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[journal article]

dc.contributor.authorReinecke, Jostde
dc.contributor.authorErdmann, Ankede
dc.contributor.authorVoelkle, Manuelde
dc.date.accessioned2024-02-22T13:45:45Z
dc.date.available2024-02-22T13:45:45Z
dc.date.issued2024de
dc.identifier.issn2190-4936de
dc.identifier.urihttps://www.ssoar.info/ssoar/handle/document/92380
dc.description.abstractBackground: Criminological research shows that there is nearly always a strong and posi­tive association between delinquency and being a victim of crime. This so-called victim-offender overlap is one of the most consistent and best documented findings in criminology. However, examinations using longitudinal panel data are rather scarce. Previous analyses based on latent growth and cross-lagged panel models showed that the developments of victimization and offending are parallel processes that expose similar stability and mutual influence over the period of adolescence and early adulthood (Erdmann & Reinecke, 2018). Objectives: The present study examines the relationship between victimization and of­fending over the phase of adolescence and emerging adulthood. The focus is on the ap­plication of continuous time dynamic modeling and on comparing results using data from the criminological panel study Crime in the Modern City. For the present analyses, seven consecutive panel waves are used that contain information about German adolescents from the age of 14 to 20 years. Approach: The relationship between victimization and offending is analyzed by con­tinuous time structural equation modeling using the R package ctsem (Driver & Voelkle, 2018, 2021). In addition to the unconditional models, relevant predictors (gender, routine activities) are considered in the conditional models. Methododological and substantive as­pects of continuous time dynamic modeling are highlighted in the discussion of the results.de
dc.languageende
dc.subject.ddcSozialwissenschaften, Soziologiede
dc.subject.ddcSocial sciences, sociology, anthropologyen
dc.subject.othercontinuous time modeling; panel analysis; R, ctsem; longitudinal datade
dc.titleContinuous Time Modeling with Criminological Panel Data: An Application to the Longitudinal Association between Victimization and Offendingde
dc.description.reviewbegutachtet (peer reviewed)de
dc.description.reviewpeer revieweden
dc.source.journalMethods, data, analyses : a journal for quantitative methods and survey methodology (mda)
dc.source.volume18de
dc.publisher.countryDEUde
dc.source.issue1de
dc.subject.classozErhebungstechniken und Analysetechniken der Sozialwissenschaftende
dc.subject.classozMethods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methodsen
dc.subject.thesozDelinquenzde
dc.subject.thesozdelinquencyen
dc.subject.thesozViktimisierungde
dc.subject.thesozvictimizationen
dc.subject.thesozStraftatde
dc.subject.thesozoffenseen
dc.subject.thesozJugendlicherde
dc.subject.thesozadolescenten
dc.subject.thesozAdoleszenzde
dc.subject.thesozadolescenceen
dc.subject.thesozjunger Erwachsenerde
dc.subject.thesozyoung adulten
dc.subject.thesozDatengewinnungde
dc.subject.thesozdata captureen
dc.subject.thesozPanelde
dc.subject.thesozpanelen
dc.subject.thesozLängsschnittuntersuchungde
dc.subject.thesozlongitudinal studyen
dc.subject.thesozModellde
dc.subject.thesozmodelen
dc.rights.licenceCreative Commons - Namensnennung 4.0de
dc.rights.licenceCreative Commons - Attribution 4.0en
internal.statusformal und inhaltlich fertig erschlossende
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dc.type.stockarticlede
dc.type.documentZeitschriftenartikelde
dc.type.documentjournal articleen
dc.source.pageinfo109-138de
internal.identifier.classoz10105
internal.identifier.journal614
internal.identifier.document32
internal.identifier.ddc300
dc.identifier.doihttps://doi.org/10.12758/mda.2023.01de
dc.description.pubstatusVeröffentlichungsversionde
dc.description.pubstatusPublished Versionen
internal.identifier.licence16
internal.identifier.pubstatus1
internal.identifier.review1
internal.pdf.validfalse
internal.pdf.wellformedtrue
internal.pdf.ocrnull Page_30
internal.pdf.encryptedfalse
ssoar.urn.registrationfalsede


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