Finding a serial burglar's home using distance decay and conditional origin–destination patterns: a test of empirical Bayes journey-to-crime estimation in the Hague

Can we tell where an offender lives from where he or she commits crimes? Journey-to-crime estimation is a tool that uses crime locations to tell us where to search for a serial offender's home. In this paper, we test a new method: empirical Bayes journey-to-crime estimation. It differs from previous methods because it utilises an ‘origin–destination’ rule in addition to the ‘distance decay’ rule that prior methods have used. In the new method, the profiler not only asks ‘what distances did previous offenders travel between their home and the crime scenes?’ but also ‘where did previous offenders live who offended at the locations included in the crime series I investigate right now?’. The new method could not only improve predictive accuracy, it could also reduce the traditional distinction between marauding and commuting offenders. Utilising the CrimeStat software, we apply the new method to 62 serial burglars in The Hague, The Netherlands, and show that the new method has higher predictive accuracy than methods that only exploit a distance decay rule. The new method not only improves the accuracy of predicting the homes of commuters—offenders who live outside their offending area—it also improves the search for marauders—offenders who live inside their offending area. After presenting an example of the application of the technique for prediction of a specific burglar, we discuss the limitations of the method and offer some suggestions for its future development. Copyright © 2009 John Wiley & Sons, Ltd.     

Multidimensional rotation and scaling of configurations to optimal agreement

An integrated method for rotating and rescaling a set of configurations to optimal agreement in subspaces of varying dimensionalities is developed. The approach relates existing orthogonal rotation techniques as special cases within a general framework based on a partition of variation which provides convenient measures of agreement. In addition to the well-known Procrustes and inner product optimality criteria, a criterion which maximizes the consensus among subspaces of the configurations is suggested. Since agreement of subspaces of the configurations can be examined and compared, rotation and rescaling is extended from a data transformation technique to an analytical method.     

Let There Be Variance: Individual Differences in Consecutive Self‐control in a Laboratory Setting and Daily Life

The large body of research used to support ego‐depletion effects is currently faced with conceptual and replication issues, leading to doubt over the extent or even existence of the ego‐depletion effect. By using within‐person designs in a laboratory (Study 1; 187 participants) and an ambulatory assessment study (Study 2; 125 participants), we sought to clarify this ambiguity by investigating whether prominent situational variables (such as motivation and affect) or personality traits can help elucidate when ego depletion can be observed and when not. Although only marginal ego‐depletion effects were found in both studies, these effects varied considerably between individuals, indicating that some individuals experience self‐control decrements after initial self‐control exertion and others not. However, neither motivation nor affect nor personality traits such as trait self‐control could consistently explain this variability when models were applied that controlled for variance due to targets and the depletion manipulation (Study 1) or days (Study 2) as well as for multiple testing. We discuss how the operationalization and reliability of our key measures may explain these null effects and demonstrate that alternative metrics may be required to study the consequences of the consecutive exertion of self‐control. © 2019 European Association of Personality Psychology     

What if I am the one? Measuring individual differences in emotional sensitivity to probability and emotional reactivity to possibility

Current theories of risk perception point to the powerful role of emotion and the neglect of probabilistic information in the face of risk, but these tendencies differ across individuals. We propose a method for measuring individuals' emotional sensitivity to probability to assess how feelings about probabilities, rather than the probabilities themselves, influence decisions. Participants gave affective ratings (worry or excitement) to 14 risky events, each with a specified probability ranging from 1 in 10 to 1 in 10,000,000. For each participant, we regressed these emotional responses against item probabilities, estimating a slope (the degree to which emotional responses change with probability) and an intercept (the emotional reaction to an event with a fixed probability). These two parameters were treated as individual difference scores and included in models predicting reactions to several health risk scenarios. Both emotional sensitivity to probability (slope) and emotional reactivity to possibility (intercept) significantly predicted responses to these scenarios, above and beyond the predictive power of other well‐established individual difference measures.