A Risk-Based Method for Modeling Traffic Fatalities

We describe a risk-based analytical framework for estimating traffic fatalities that combines the probability of a crash and the probability of fatality in the event of a crash. As an illustrative application, we use the methodology to explore the role of vehicle mix and vehicle prevalence on long-run fatality trends for a range of transportation growth scenarios that may be relevant to developing societies. We assume crash rates between different road users are proportional to their roadway use and estimate case fatality ratios (CFRs) for the different vehicle-vehicle and vehicle-pedestrian combinations. We find that in the absence of road safety interventions, the historical trend of initially rising and then falling fatalities observed in industrialized nations occurred only if motorization was through car ownership. In all other cases studied (scenarios dominated by scooter use, bus use, and mixed use), traffic fatalities rose monotonically. Fatalities per vehicle had a falling trend similar to that observed in historical data from industrialized nations. Regional adaptations of the model validated with local data can be used to evaluate the impacts of transportation planning and safety interventions, such as helmets, seat belts, and enforcement of traffic laws, on traffic fatalities.     

Understanding child neglect in Aboriginal families and communities in the context of trauma

Child neglect is a significant concern for Aboriginal families and communities both in Australia and internationally. Service responses to child neglect are largely informed by child neglect theories, which explain the nature and causes of child neglect. However, child neglect is a problem that is worsening for Aboriginal children, suggesting that these theories are not appropriate. This paper argues that to meet the needs of Aboriginal families and communities where there is child neglect, policy and practice needs to acknowledge and address the impact of trauma in shaping the lived experiences of Aboriginal people. International literature discusses the impact and consequence of historical trauma within Indigenous families and communities, and separately, child maltreatment theorists have discussed the ecological nature of child neglect. However, the literature and evidence‐base linking the two, child neglect and historical trauma in Indigenous contexts, are very scant. This paper aims to fill this gap and emphasize the importance of addressing child neglect within Aboriginal families and communities in the context of historical trauma. Although this paper focuses on the post‐colonial experiences of Aboriginal people in Australia, the arguments can extend to many Indigenous cultures universally where child welfare interventions have resulted in significant and ongoing trauma.     

Critical Discourse,Applied Inquiry and Public Health Action with Urban Middle School Students: Lessons Learned Engaging Youth in Critical Service-Learning

The Nuestro Futuro Saludable partnership designed a critical service-learning intervention focused on health equity and action. The 10-week afterschool intervention was implemented in a Boston middle school. Youths who took part in the intervention were knowledgeable about the social determinants of health in their communities, as well as to the barriers to health. Our findings indicate that engaging young people in a meaningful way will be critical if health improvement efforts are to be realized. We found that a critical service-learning framework that incorporates elements of applied inquiry and critical pedagogy was effective as a health intervention and provided opportunities for action.     

Discipline-Specific Literature Bases: A View of the APS Model

Abstract

Librarians see the large quantities of literature and the complete writing/publishing/world as a complete system. Changes to one piece (e.g., making publishing or reading electronic) will not fundamentally change the process. The pieces of the system are there, not for technological reasons, but for reasons of authority, validation, and self-correction in the process of scholarly communication. Electronic publishing will cause great changes, but the changes will not eliminate roles that now exist. The changes will be to enhance our abilities to better do that which we do now, whether that be to edit, review, referee, write, or manage the information flow.     

A spatial Bayesian semiparametric mixture model for positive definite matrices with applications in diffusion tensor imaging

Studies on diffusion tensor imaging (DTI) quantify the diffusion of water molecules in a brain voxel using an estimated 3 × 3 symmetric positive definite (p.d.) diffusion tensor matrix. Due to the challenges associated with modelling matrix‐variate responses, the voxel‐level DTI data are usually summarized by univariate quantities, such as fractional anisotropy. This approach leads to evident loss of information. Furthermore, DTI analyses often ignore the spatial association among neighbouring voxels, leading to imprecise estimates. Although the spatial modelling literature is rich, modelling spatially dependent p.d. matrices is challenging. To mitigate these issues, we propose a matrix‐variate Bayesian semiparametric mixture model, where the p.d. matrices are distributed as a mixture of inverse Wishart distributions, with the spatial dependence captured by a Markov model for the mixture component labels. Related Bayesian computing is facilitated by conjugacy results and use of the double Metropolis–Hastings algorithm. Our simulation study shows that the proposed method is more powerful than competing non‐spatial methods. We also apply our method to investigate the effect of cocaine use on brain microstructure. By extending spatial statistics to matrix‐variate data, we contribute to providing a novel and computationally tractable inferential tool for DTI analysis.     

NONLINEAR TUBE-FITTING FOR THE ANALYSIS OF ANATOMICAL AND FUNCTIONAL STRUCTURES

We are concerned with the estimation of the exterior surface and interior summaries of tube-shaped anatomical structures. This interest is motivated by two distinct scientific goals, one dealing with the distribution of HIV microbicide in the colon and the other with measuring degradation in white-matter tracts in the brain. Our problem is posed as the estimation of the support of a distribution in three dimensions from a sample from that distribution, possibly measured with error. We propose a novel tube-fitting algorithm to construct such estimators. Further, we conduct a simulation study to aid in the choice of a key parameter of the algorithm, and we test our algorithm with validation study tailored to the motivating data sets. Finally, we apply the tube-fitting algorithm to a colon image produced by single photon emission computed tomography (SPECT) and to a white-matter tract image produced using diffusion tensor imaging (DTI).     

Complementarity of pensions and training under multiemployer plans

We compare firmoptimizing and institutional models of labor contracts to investigate how different types of pension plans affect employee training. Unlike previous stud-ies, we consider an expanded voice model of training and pension coverage in which worker and union preferences feed back on firm decisions, and we test for this bidi-rectional causality between pensions and training. A standard view is that firms pro-vide pensions to optimize their training costs. However, when pension coverage is treated as endogenous in a twostage least squares regression (the data are merged 1991 CPS samples), pensions have a negative effect on training. In contrast, when the pension is a definedbenefit, multiemployer plan, training and pensions are comple-ments, consistent with both optimizing and institutional models. We are grateful for excellent research assistance from Michael Ash, Bhashkar Mazumder, and Judith Ruha and for suggestions from Dale Belman, David Card, B.J. Lee, David MacPherson, and John Turner.     

The brief sexual attitudes scale

The measurement of sexual attitudes is important, and ease of scale usability is one key aspect of measurement. This paper details three studies conducted to develop a briefer and thus more efficient version of the multidimensional Sexual Attitudes Scale (43 items). The first two studies (I and II) employed existing data sets to develop a 23-item version of the Sexual Attitudes Scale, using exploratory factor analysis in Study I and confirmatory factor analysis in Study II. The same four subscales of Permissiveness, Birth Control (formerly called Sexual Practices), Communion, and Instrumentality were retained in the 23-item measure, called the Brief Sexual Attitudes Scale. Study III was a prospective data collection using only the 23 items composing the Brief Sexual Attitudes Scale. The four subscales were hypothesized to correlate with a number of relationship measures in predictable ways. Results indicated that the Brief Sexual Attitudes Scale is a reliable and valid measure of the four sexual attitudes, and has strong psychometric properties. It should be effective and efficient for both research and clinical uses.     

Surface Estimation, Variable Selection, and the Nonparametric Oracle Property

Variable selection for multivariate nonparametric regression is an important, yet challenging, problem due, in part, to the infinite dimensionality of the function space. An ideal selection procedure should be automatic, stable, easy to use, and have desirable asymptotic properties. In particular, we define a selection procedure to be nonparametric oracle (np-oracle) if it consistently selects the correct subset of predictors and at the same time estimates the smooth surface at the optimal nonparametric rate, as the sample size goes to infinity. In this paper, we propose a model selection procedure for nonparametric models, and explore the conditions under which the new method enjoys the aforementioned properties. Developed in the framework of smoothing spline ANOVA, our estimator is obtained via solving a regularization problem with a novel adaptive penalty on the sum of functional component norms. Theoretical properties of the new estimator are established. Additionally, numerous simulated and real examples further demonstrate that the new approach substantially outperforms other existing methods in the finite sample setting.