Machine learning algorithms are becoming ubiquitous in modern life. When used to help inform human decision making, they have been criticized by some for insufficient accuracy, an absence of transparency, and unfairness. Many of these concerns can be legitimate, although they are less convincing...

In this paper, we report on the development of a short screening tool that deputies in the Los Angeles Sheriff's Department could use in the field to help forecast domestic violence incidents in particular households. The data come from over 500 households to which sheriff's deputies were...

Purpose Much of what is known regarding the transition away from crime is limited to young adulthood and specific life events and samples of non-serious offenders comprised mainly of white males.Methods The current study assesses the potential links between educational achievement, post-release...

Regressions can be weighted by propensity scores in order to reduce bias. However, weighting is likely to increase random error in the estimates, and to bias the estimated standard errors downward, even when selection mechanisms are well understood. Moreover, in some cases, weighting will...

As a special case of statistical learning, ensemble methods are well suited for the analysis of opportunistically collected data that involve many weak and sometimes specialized predictors, especially when subject-matter knowledge favours inductive approaches. We analyse data on the incidental...

This article provides an introduction to ensemble statistical procedures as a special case of algorithmic methods. The discussion begins with classification and regression trees (CART) as a didactic device to introduce many of the key issues. Following the material on CART is a consideration of...

In this article, the authors report on the development of a short screening tool that deputies in the Los Angeles Sheriff’s Department could use in the field to help forecast domestic violence incidents in particular households. The data come from more than 500 households to which...