Please use this identifier to cite or link to this item: https://anrows.intersearch.com.au/anrowsjspui/handle/1/13483
Record ID: 6f4c660e-d42d-41cb-8151-7c7fe98099fa
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dc.contributor.authorGraham, Timothyen
dc.contributor.authorFitzgerald, Robinen
dc.date.accessioned2022-06-30T23:06:48Z-
dc.date.available2022-06-30T23:06:48Z-
dc.date.issued2016en
dc.identifier.citationNo, 189en
dc.identifier.urihttps://anrows.intersearch.com.au/anrowsjspui/handle/1/13483-
dc.languageenen
dc.publisherNSW Bureau of Crime Statistics and Researchen
dc.subjectAustraliaen
dc.subjectRecidivismen
dc.subjectViolenceen
dc.subjectDomestic violenceen
dc.titleAssessing the risk of domestic violence recidivismen
dc.typeJournal Articleen
dc.identifier.catalogid13421en
dc.identifier.urlhttp://www.bocsar.nsw.gov.au/Documents/CJB/Report-2016-Assessing-the-risk-of-domestic-violence-recidivism-cbj189.pdfen
dc.subject.keywordnew_recorden
dc.subject.keywordInvalid URLen
dc.description.notes"Aim: To determine what factors independently predict violent DV-related re-offending among a cohort of people convicted<br/ >of a(ny) DV offence and given a non-custodial penalty.<br/ >Method: Data from the NSW Bureau of Crime Statistics and Research (BOCSAR) Reoffending Database were used to<br/ >examine violent DV-related reconviction. A cohort of DV offenders convicted in 2011-12 was first identified using domestic<br/ >violence lawpart codes, and followed up for two years. To identify the best fitting model we first examined bi-variate<br/ >relationships between explanatory variables and the dependent variable. We then estimated a multivariate logistic regression<br/ >model to determine which variables independently predicted reconviction. Finally, we tested the predictive validity of the<br/ >model using a range of cross-validation strategies. "en
dc.identifier.sourceContemporary Issues in Crime and Justiceen
dc.date.entered2016-08-11en
dc.publisher.placeSydneyen
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