1. Planning for the future of the US correctional system / April Pattavina and Faye S. Taxman -- 2. A case study in gaps in services for drug-involved offenders / Faye S. Taxman and Matthew L. Perdoni -- 3. The simulation modelling process / Andrew Greasley -- 4. The empirical basis for the RNR model with an updated RNR conceptual framework / Faye S. Taxman, April Pattavina, Michael S. Caudy, James Byrne and Joseph Durso -- 5. Creating simulation parameter inputs, needs, and recidivism / Stephanie A. Ainsworth and Faye S. Taxman -- 6. The responsivity principle: determining the appropriate program and dosage to match risk and needs / Erin L. Crites and Faye S. Taxman -- 7. Reducing recidivism through correctional programming: using meta-analysis to inform the RNR simulation tool / Michael S. Caudy, Liansheng Tang, Stephanie A. Ainsworth, Jennifer Lerch and Faye S. Taxman -- 8. RNR simulation tool: a synthetic datasets and its uses for policy simulations / Avinash Bhati, Erin L. Crites and Faye S. Taxman -- 9. A simulation modeling approach for planning and costing jail diversion programs for persons with mental illness / David Hughes -- 10. Using discrete-event simulation modeling to estimate the impact of RNR program implementation on recidivism levels / April Pattavina and Faye S. Taxman -- 11. Risk-need-responsivity (RNR): leading towards another generation of the model / Faye S. Taxman, Michael S. Caudy and April Pattavina.
This resource is supported by the Institute of Museum and Library Services under the provisions of the Library Services and Technology Act as administered by State Library of Iowa.