DEVELOPMENTAL TRAJECTORY GROUPS: FACT OR A USEFUL STATISTICAL FICTION?*

A rapidly growing literature in criminology and psychology uses a group‐based methodology to identify and analyze developmental trajectories. Some confusion has arisen about the interpretation of this novel statistical model and with it some degree of cautionary commentary. We begin with a discussion of the role of trajectory groups as a statistical device for approximating population differences in developmental trajectories. We then discuss three misconceptions about group‐based trajectory modeling that stem from misunderstandings about the approximating role of trajectory groups: (1) individuals actually belong to a trajectory group, (2) the number of trajectory groups is immutable, and (3) the trajectories of group members follow the group‐level trajectory in lock step. We also point out that groupbased statistical modeling is not bound at the hip to the testing of taxonomic theories, and can just as well be used to test nontaxonomic theories.     

Texas Criminal Defense Attorneys’ Perceptions of Crime Victim Involvement in Criminal Prosecutions

The purpose of this study was to test the utility of the Victim Satisfaction Model of the criminal justice system by quantitatively assessing criminal defense attorneys’ perceptions of victims’ involvement in the charging and plea bargaining stages of the criminal process. A cross-section research design was used in this study. Self-administered questionnaires were mailed to defense attorneys who regularly practice criminal law in Texas. The results of this study support the utility of the Victim Satisfaction Model of the criminal justice system and further our understanding of victim involvement in the decision making and have important implications for the American criminal justice system.     

Analysis and analytical tools for managing corporate public affairs

This paper examines the place of analysis in corporate public affairs practice. It examines analysis in the larger context of organisational decision making, examines models, tools and techniques available to the CPA practitioner, and identifies factors why analysis has not received the prominence it deserves in the field and beyond. Copyright © 2002 Henry Stewart Publications     

Governments,decentralisation, and the risk of electoral defeat

In the last three decades several countries around the world have transferred authority from their national to their regional governments. However, not all their regions have been empowered to the same degree and important differences can be observed between and within countries. Why do some regions obtain more power than others? Current literature argues that variation in the redistribution of power and resources between regions is introduced by demand. Yet these explanations are conditional on the presence of strong regionalist parties or territorial cleavages. This article proposes instead a theory that links the government’s risk of future electoral defeat with heterogeneous decentralisation, and tests its effects using data from 15 European countries and 141 regions. The results provide evidence that parties in government protect themselves against the risk of electoral defeat by selectively targeting decentralisation towards regions in which they are politically strong. The findings challenge previous research that overestimates the importance of regionalist parties while overlooking differences between regions.     

CRIME DIVERSITY*

Large geographic areas should host a greater diversity of crime compared with small geographic areas. This proposition is reasonable given that larger geographic areas should not only support more crime but also contain a greater diversity of criminogenic settings. This article uses a neutral model to characterize crime richness as a function of area. The model starts with two neutral assumptions: 1) that all environments are statistically equivalent and exert no influence on what types of crimes occur there; and 2) that different crime types occur independently of one another. The model produces rigorous predictions for the mean and variance in crime richness with increasing area. Tests of the model against a sample of 172,055 crimes occurring in Los Angeles during the year 2013 are qualitatively consistent with neutral expectations. The model is made quantitatively consistent by constant scaling. Resampling experiments show that at most 20 percent of the mean crime richness is attributable to nonrandom clustering and assortment of crime types. A modified neutral model allowing for variation crime concentration is consistent with observed variance in crime richness. The results suggest that very general and largely neutral laws may be driving crime diversity in space.     

Economic and Sociological Correlates of Suicides: Multilevel Analysis of the Time Series Data in the United Kingdom

For the effects of social integration on suicides, there have been different and even contradictive conclusions. In this study, the selected economic and social risks of suicide for different age groups and genders in the United Kingdom were identified and the effects were estimated by the multilevel time series analyses. To our knowledge, there exist no previous studies that estimated a dynamic model of suicides on the time series data together with multilevel analysis and autoregressive distributed lags. The investigation indicated that unemployment rate, inflation rate, and divorce rate are all significantly and positively related to the national suicide rates in the United Kingdom from 1981 to 2011. Furthermore, the suicide rates of almost all groups above 40 years are significantly associated with the risk factors of unemployment and inflation rate, in comparison with the younger groups.     

Auricular Surface Aging: Comparing Two Methods that Assess Morphological Change in the Ilium with Bayesian Analyses

Modern standards in forensic anthropology require rigorous testing and evaluation of methods used for aging skeletal remains. Age estimation has been criticized for bias, inaccuracy, and population specificity; issues which are minimized by the application of Bayesian methodology. Using Bayesian statistics, we compare the Lovejoy et al. (Am J Phys Anthropol, 68, 1985, 15) (original) and Buckberry and Chamberlain (Am J Phys Anthropol, 119, 2002, 231) (revised) auricular surface aging methods. Transition analysis parameters derived from American males (n = 372), in combination with a Thai male (N = 37) informative prior, statistically model age in Portuguese males (n = 221). Cumulative binomial tests assess the accuracy of the generated age ranges. Overall, the application of transition analysis and Bayesian statistics significantly improved age estimation with both methods (also outperforming Suchey‐Brooks pubic symphysis aging). Moreover, the accuracy of the original method was low without statistical modeling, whereas the revised method can be applied accurately without further statistical analysis. Additionally, reference tables for aging Portuguese males are provided.     

Dynamic risk and protective factors

ABSTRACT

This paper reviews the literature regarding the identification and measurement of risk factors considered imminent precipitants of subsequent criminal conduct (i.e. dynamic risk factors). This paper also frames these risk factors against the so-called protective factors that are presumed to mitigate risk. Commonality among recent dynamic risk and protective measures reflects general agreement regarding viable candidate variables. Empirical studies suggest such factors yield incremental predictive validity and should inform case-formulaic understanding of criminal conduct and pathways to desistance, although this is not common practice. As well, definitional and measurement considerations are not well advanced and speak to the need for further conceptual clarity.     

From dynamic risk factors to causal processes: a methodological framework

ABSTRACT

It is becoming increasingly apparent that dynamic risk factors are unable to function as explanations of offending because they are composite constructs, which contain a mixture of putative causes, states of affairs, and problematic cognitive, affective, behavioural and social states associated with crime. In this paper we draw from psychopathology research and theory on the conception and classification of mental disorders to develop the Dynamic Risk Research Framework (DRRF). In our opinion, the assumptions and methodological tool associated with this framework can better focus research into the causes of offending by making use of the information provided by dynamic risk factors. A conceptual framework such as the DRRF can arguably translate this valuable information into deep, coherent explanations, and ultimately, more streamlined and precise intervention strategies.     

Traits and states at work: lure,risk and personality as predictors of occupational crime

This study linked individual characteristics to proximate factors operating in the moment of decision-making to predict occupational crime. We distinguished between people’s task-related conscience, as embodied by the Conscientiousness personality trait, and a more general moral conscience as embodied by the Honesty-Humility trait, hypothesizing that both traits are differentially related to the way situational characteristics, such as costs and benefits, are perceived. We operationalized the concept of ‘felt lure’ emanating from the benefits of a crime, defining it as an affective state that tempts people to commit a criminal act, and examined it next to perceived risk of sanction as a proximate predictor of criminal choice. In line with our predictions, Conscientiousness and Honesty-Humility significantly predicted occupational criminal choice as did felt lure and perceived risk. Specifically, perceived risk and felt lure mediated the relations between Conscientiousness and Honesty-Humility on the one hand, and occupational criminal choice on the other.