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Evidence for risk estimate precision: implications for individual risk communication.

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Actuarial risk assessment tools accurately predict recidivism. Sufficient sample sizes improve the precision of individual risk estimates, aiding correctional policy and resource allocation.

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Area of Science:

  • Criminology
  • Forensic Psychology
  • Risk Assessment

Background:

  • Actuarial risk assessment instruments effectively discriminate between offenders who will reoffend and those who will not.
  • These tools utilize individual-level predictors like age, criminal history, and psychopathy.
  • While relative risk is informative for policy, the precision of absolute risk for individuals has been difficult to establish.

Purpose of the Study:

  • To examine the relationship between sample size and the precision of actuarial risk estimates.
  • To investigate the precision of individual risk estimates using the Post Conviction Risk Assessment (PCRA) tool.
  • To clarify the implications of absolute risk for communicating offender risk levels.

Main Methods:

  • Analysis of actuarial risk estimate precision across varying sample sizes.
  • Utilized the Post Conviction Risk Assessment (PCRA) tool.
  • Included large samples of up to 26,642 offenders.

Main Results:

  • The precision of individual actuarial risk estimates improves significantly with sufficient sample size.
  • Demonstrated that precise individual risk estimates are achievable in large offender samples.
  • Highlighted the importance of sample size in validating risk assessment tools.

Conclusions:

  • Sufficient sample size is crucial for achieving precise individual risk estimates in actuarial assessments.
  • The communication of individual offender risk should focus on informing policy by matching cases to aggregate data.
  • This risk communication function is separate from individual needs assessment and treatment planning.