Using decision tree algorithms to screen individuals at risk of entry into sexual recidivism
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DOI: 10.1016/j.jcrimjus.2019.05.003
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- Amirault, Joanna & Lussier, Patrick, 2011. "Population heterogeneity, state dependence and sexual offender recidivism: The aging process and the lost predictive impact of prior criminal charges over time," Journal of Criminal Justice, Elsevier, vol. 39(4), pages 344-354, July.
- G. V. Kass, 1980. "An Exploratory Technique for Investigating Large Quantities of Categorical Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(2), pages 119-127, June.
- Lussier, Patrick & Gress, Carmen L.Z., 2014. "Community re-entry and the path toward desistance: A quasi-experimental longitudinal study of dynamic factors and community risk management of adult sex offenders," Journal of Criminal Justice, Elsevier, vol. 42(2), pages 111-122.
- Lussier, Patrick & Blokland, Arjan, 2014. "The adolescence-adulthood transition and Robins’s continuity paradox: Criminal career patterns of juvenile and adult sex offenders in a prospective longitudinal birth cohort study," Journal of Criminal Justice, Elsevier, vol. 42(2), pages 153-163.
- Mathesius, Jeffrey & Lussier, Patrick, 2014. "The Successful Onset of Sex Offending: Determining the Correlates of Actual and Official Onset of Sex Offending," Journal of Criminal Justice, Elsevier, vol. 42(2), pages 134-144.
- Lussier, Patrick & Bouchard, Martin & Beauregard, Eric, 2011. "Patterns of criminal achievement in sexual offending: Unravelling the “successful” sex offender," Journal of Criminal Justice, Elsevier, vol. 39(5), pages 433-444.
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