Abstract
Using two data sets, containing 582 total cases, this study investigates whether classifying offenders on trajectories of risk scores helps predict parolee recidivism. One data set has 4 years of risk scores and another has three. Both data sets contain control variables measuring released inmates’ characteristics. The dependent variable measures arrest or return to prison over a 2-year span. A growth mixture model, classifies offenders into three classes, a stable and high trajectory group, a group with a high but declining risk trajectory, and a small, low-risk group with little change. Trajectory class membership correlates with recidivism in both data sets. Supplementary analyses show that assigned classes are better predictors of recidivism than last risk scores or simple change scores. Discussion centers on the appeal and relevance of trajectories of risk, as opposed to static measures, for predicting offender misconduct and other outcomes.
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Ægisdóttir, S., White, M. J., Spengler, P. S., Mugherman, A. S., Anderson, L. A., Cook, R. S., et al. (2006). The meta-analysis of clinical judgment project: Fifty-six years of accumulated research on clinical versus statistical prediction. Counseling Psychologist, 34(3), 341–382.
Andrews, D. A., & Bonta, J. (1995). Level of service inventory-revised: user’s manual. Toronto: ON: Multi-Health Services.
Andrews, D. A., & Bonta, J. (2003). The psychology of criminal conduct. Cincinnati: Anderson Co.
Andrews, D. A., & Bonta, J. ( 2006). The psychology of criminal conduct (4th ed.). Newark, NJ: LexisNexis/ Matthew Bender.
Andrews, D. A., Bonta, J., & Wormith, S. J. (2006). The recent past and near future of risk/need assessment. Crime & Delinquency, 52, 7–27.
Andrews, D. A., Bonta, J., Wormith, J. S., Guzzo, L., Brews, A., Rettinger, J., et al. (2011). Sources of variability in estimates of predictive validity: a specification with level of service general risk and need. Criminal Justice and Behavior, 38(5), 413–432.
Asparouhov, T., & Muthén, B. (2008). Multilevel mixture models. In G. R. Hancock and K. M. Samuelson (Eds.), Advances in Latent Variable Mixture Models (pp. 27–51). Charlotte, NC: Information Age Publishing.
Blanchette, K., & Brown, S. (2006). The assessment and treatment of women offenders: an integrative perspective. West Sussex: Wiley.
Folsom, J., & Atkinson, J. (2007). The generalizability of the LSI-R and the Cat to the prediction of recidivism in female offenders. Criminal Justice and Behavior, 34(8), 1044–1056.
Gendreau, P., Goggin, C., & Smith, P. (2002). Is the PCL-R really the “unparalleled” measure of offender risk? A lesson in knowledge cumulation? Criminal Justice and Behavior, 29(4), 397–426.
Hsu, C., Caputi, P., & Byrne, M. K. (2011). The Level of Service Inventory-Revised (Lsi-R) and Australian offenders: factor structure, sensitivity and specificity. Criminal Justice and Behavior, 38(6), 600–618.
Jung, T., & Wickrama, K. A. S. (2008). An introduction to latent class growth analysis and growth mixture modeling. Social and Personality and Psychology Compass, 2(1), 302–317.
Labrecque, R. M., Smith, P., Lovins, B. K., & Latessa, E. J. (2014). The importance of reassessment: How changes in the LSI-R risk score Can improve the prediction of recidivism. Journal of Offender Rehabilitation, 53(2), 116–128.
Lussier, P., & Gress, C. L. (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, 42(2), 111–122.
Manchak, S. M., Skeem, J. L., Douglass, K. S., & Siransosian, M. (2009). Does gender moderate the predictive utility of the level of service inventory-revised (LSI-R) for serious violent offenders? Criminal Justice and Behavior, 36(5), 425–442.
Mauratto, P., & Moffat, K. H. (2006). Assembling risk and the restructuring of penal control. British Journal of Criminology, 46(3), 438–454.
Prell, L. (2009). LSI-R scores: change matters. Iowa Department of Corrections: Data Download, 12(1), 1–2.
Reisig, M., Holtfretter, K., & Morash, M. (2006). Assessing recidivism risk across female pathways to crime. Justice Quarterly, 23(3), 384–405.
Rice, M. E., Harris, G. T., & Lang, C. (2013). Validation of and revision to the VRAG and SORAG: the Violence Risk Appraisal Guide—Revised (VRAG-R). Psychological Assessment, 25, 951–965.
Rocque, M., & Plummer-Beale, J. (2014). In the eye of the beholder? An examination of the inter-rater reliability of the LSI-R and YLS/CMI in a correctional agency. Journal of Criminal Justice, 42(6), 568–578.
Schlager, M. D., & Simourd, D. J. (2007). Validity of the Level of Service Inventory—Revised among African American and Hispanic male offenders. Criminal Justice and Behavior, 34(4), 545–554.
Silver, E. (1998). Actuarial risk assessment: reflections on an emerging social-scientific tool. Critical Criminology, 9(1–2), 123–143.
Simourd, D. (2004). Use of dynamic risk/need assessment instruments among long-term incarcerated offenders. Criminal Justice and Behavior, 31(4), 306–323.
Simourd, D. (2006). Validation of risk. Needs assessment in the Pennsylvania department of corrections: final report—grant 15,288. Harrisburg: Pennsylvania Department of Correction.
Singh, J. P., Grann, M., & Fazel, S. (2011). A comparative study of violence risk assessment tools: a systematic review and metaregression analysis of 68 studies involving 25,980 participants. Clinical Psychology Review, 31(3), 499–513.
Smith, P., & Cullen, F. T. (2013). Predictive validity and the impact of change in total LSI-R score on recidivism. Criminal Justice and Behavior, 40(12), 1383–1396.
Smith, P., Cullen, F. T., & Latessa, E. J. (2009). Can 14,737 women be wrong? A meta‐analysis of the LSI‐R and recidivism for female offenders. Criminology & Public Policy, 8(1), 183–208.
Stahler, G. J., Mennis, J., Belenko, S., Welsh, W. N., Hiller, M. L., & Zajac, G. (2013). Predicting recidivism for released state prison offenders examining the influence of individual and neighborhood characteristics and spatial contagion on the likelihood of reincarceration. Criminal Justice and Behavior, 40(6), 690–711.
Tillyer, M. S., & Vose, B. (2011). Social ecology, individual risk, and recidivism: a multilevel examination of main and moderating influences. Journal of Criminal Justice, 39(5), 452–459.
Vaughn, M. G., DeLisi, M., Beaver, K. M., Perron, B. E., & Abdon, A. (2012). Toward a criminal justice epidemiology: behavioral and physical health of probationers and parolees in the United States. Journal of Criminal Justice, 40(3), 165–173.
Vose, B. (2008). Assessing the predictive validity of the Level of Service Inventory Revised: recidivism among Iowa parolees and probationers. Cincinnati: OH. University of Cincinnati.
Vose, B., Lowenkamp, C. T., Smith, P., & Cullen, F. T. (2009). Gender and the predictive validity of the LSI-R: a study of parolees and probationers. Journal of Contemporary Criminal Justice, 25(4), 459–471.
Vose, B., Smith, P., & Cullen, F. T. (2013). Predictive validity and the impact of change in total LSI-R score on recidivism. Criminal Justice and Behavior, 40(12), 1383–1396.
Whitacre, K. (2006). Testing the Level of Service Inventory-Revised (LSI-R) for Racial/Ethnic bias. Criminal Justice Policy Review, 17(3), 330–342.
Wilson, H. A., & Guiterrez, L. (2014). Does one size fit all? A meta-analysis examining the predictive ability of the level of service inventory (LSI) with aboriginal offenders. Criminal Justice and Behavior, 41(2), 196–219.
Wodahl, E. J., Boman, J. H., & Garland, B. E. (2015). Responding to probation and parole violations: Are jail sanctions more effective than community-based graduated sanctions? Journal of Criminal Justice, 43(3), 242–250.
Zettler, H. R., Morris, R. G., Piquero, A. R., & Cardwell, S. M. (2015). Assessing the celerity of arrest on 3-year recidivism patterns in a sample of criminal defendants. Journal of Criminal Justice, 43(5), 428–436.
Zhang, J., & Liu, N. (2014). Reliability and validity of the Chinese version of the LSI-R with Probationers. International Journal of Offender Therapy and Comparative Criminology, 59(13), 1474–1486.
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Hochstetler, A., Peters, D.J. & DeLisi, M. Classifying Risk Development and Predicting Parolee Recidivism with Growth Mixture Models. Am J Crim Just 41, 602–620 (2016). https://doi.org/10.1007/s12103-015-9320-8
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DOI: https://doi.org/10.1007/s12103-015-9320-8