The Predictive Validity of the Structured Assessment of Violence Risk in Youth for Young Spanish Offenders

In order to facilitate comparisons across follow-up studies that have used different measures of effect size, we provide a table of effect size equivalencies for the three most common measures: ROC area (AUC), Cohen's d, and r. We outline why AUC is the preferred measure of predictive or diagnostic accuracy in forensic psychology or psychiatry, and we urge researchers and practitioners to use numbers rather than verbal labels to characterize effect sizes.

In a mathematical approach to hypothesis tests, we start with a clearly defined set of hypotheses and choose the test with the best properties for those hypotheses. In practice, we often start with less precise hypotheses. For example, often a researcher wants to know which of two groups generally has the larger responses, and either a t-test or a Wilcoxon-Mann-Whitney (WMW) test could be acceptable. Although both t-tests and WMW tests are usually associated with quite different hypotheses, the decision rule and p-value from either test could be associated with many different sets of assumptions, which we call perspectives. It is useful to have many of the different perspectives to which a decision rule may be applied collected in one place, since each perspective allows a different interpretation of the associated p-value. Here we collect many such perspectives for the two-sample t-test, the WMW test and other related tests. We discuss validity and consistency under each perspective and discuss recommendations between the tests in light of these many different perspectives. Finally, we briefly discuss a decision rule for testing genetic neutrality where knowledge of the many perspectives is vital to the proper interpretation of the decision rule.