Bayes and Base Rates: What Is an Informative Prior for Actuarial Violence Risk Assessment?

Bayes' theorem describes an axiomatic relationship among marginal and conditional proportions within a single "experiment." In many ways, it has been fruitful to greatly extend this idea to the task of drawing inferences from data much more generally. Commonly, what matters is how all prior knowledge is revised (or not) by new findings resulting in posterior (sometimes "subjective") probabilities. And, to address many important problems, it is sensible to conceive of probability in such subjective terms. However, some commentators in the domain of violence risk assessment have assumed an analogous axiomatic relationship among marginals (i.e., priors in the form of base rates) observed in one study and conditionals (i.e., posteriors in the form of revised rates) expected in a separate study or assessment context. We present examples from our own research to suggest this assumption is generally unwarranted and ultimately an unaddressed empirical matter.