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An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Improving Risk Communication: Developing Risk Ratios for the VRAG-R
Simon T Davies1, L Maaike Helmus2, Vernon L Quinsey3
1Victoria University of Wellington, New Zealand.
Abstract:
We developed a set of risk ratios for the Violence Risk Appraisal Guide-Revised (VRAG-R) to broaden the range of risk communication options available when using this tool and to provide information needed for future efforts to apply The Council of State Governments Justice Center's standardized five-level risk framework to the scale. A slightly reduced version of the VRAG-R normative data set was used for the analyses (N = 1,238). Contrary to previous research developing risk ratios, logistic regression provided a more accurate estimate of observed violent recidivism rates than Cox regression for both total VRAG-R scores and VRAG-R decile bins. Further analyses indicated the relationship between the VRAG-R and violent recidivism was consistent over a 15-year follow-up period. Due to the difficulties with interpreting odds ratios, the final risk ratios were computed using rate ratios derived from a logistic regression model using a 5-year fixed follow-up period. These risk ratios, and templates for how the ratios might be used in an assessment report, are presented in the appendices.
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