A Commentary on Statistical Assessment of Violence Recidivism Risk

TL;DR

This paper critically examines claims that statistical tools for assessing violence recidivism risk are inherently unreliable, arguing that such claims are mistaken and should not hinder the use of statistical assessments in this field.

Contribution

It provides a technical critique of previous arguments claiming the unreliability of statistical risk assessments for violence recidivism.

Findings

Previous claims of imprecision are technically flawed

Statistical assessments can be useful for violence risk prediction

The paper clarifies misconceptions about statistical evaluation methods

Abstract

Increasing integration and availability of data on large groups of persons has been accompanied by proliferation of statistical and other algorithmic prediction tools in banking, insurance, marketiNg, medicine, and other FIelds (see e.g., Steyerberg (2009a;b)). Controversy may ensue when such tools are introduced to fields traditionally reliant on individual clinical evaluations. Such controversy has arisen about "actuarial" assessments of violence recidivism risk, i.e., the probability that someone found to have committed a violent act will commit another during a specified period. Recently Hart et al. (2007a) and subsequent papers from these authors in several reputable journals have claimed to demonstrate that statistical assessments of such risks are inherently too imprecise to be useful, using arguments that would seem to apply to statistical risk prediction quite broadly. This commentary examines these arguments from a technical statistical perspective, and finds them seriously mistaken in many particulars. They should play no role in reasoned discussions of violence recidivism risk assessment.