Precarity and structural racism in Black youth encounters with police

Youth experience increased surveillance by and involuntary contact with police officers compared with other age groups. Studies that explore the experiences of youth during these encounters are scant and focus on youth with criminal histories. This research aims to explore the experiences of college-attending youth between 18 and 24 years old in two southern states. The study was designed and conducted according to the tenets of interpretative phenomenological analysis (IPA). Twelve Black youth were recruited and interviewed between April 2015 and April 2016. Three superordinate themes (and subthemes) were identified: (1) negative feelings towards the police; (2) precarity of police encounters (subthemes: police as a threat to welfare; it could be me; steps to follow during police encounters; behavior is irrelevant) and; (3) police response is part of structural racism (subthemes: racism is everywhere; media contributes to racism). The importance of these findings for social work practice and research will be discussed.     

Comparing measures of general and abdominal adiposity as predictors of blood pressure in college students

Objective: To compare anthropometric measures of body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), and sagittal abdominal diameter (SAD) as predictors of blood pressure in college students. Participants: Students (N = 116) were recruited from November 2012 to May 2014 at an urban university and rural community colleges. Methods: Students underwent a brief physical examination during which anthropometric measures were obtained and blood pressure was measured. Covariates were measured using self-reported questionnaires. Hierarchical multiple linear regressions were used for the data analysis. Results: All anthropometric measures were predictive of systolic (SBP) and diastolic blood pressure (DBP). WC was the strongest predictor of SBP (β = .582, p < .01) explaining an additional 3–4% of the variance than BMI, WHtR, or SAD. The measures were similar in predicting DBP. WC predicted SBP independent of BMI. Conclusions: Clinicians should consider using WC to assess the risk for hypertension in college students.     

Accelerated test system strength models based on Birnbaum–Saunders distribution: a complete Bayesian analysis and comparison

Several models for studies related to tensile strength of materials are proposed in the literature where the size or length component has been taken to be an important factor for studying the specimens’ failure behaviour. An important model, developed on the basis of cumulative damage approach, is the three-parameter extension of the Birnbaum–Saunders fatigue model that incorporates size of the specimen as an additional variable. This model is a strong competitor of the commonly used Weibull model and stands better than the traditional models, which do not incorporate the size effect. The paper considers two such cumulative damage models, checks their compatibility with a real dataset, compares them with some of the recent toolkits, and finally recommends a model, which appears an appropriate one. Throughout the study is Bayesian based on Markov chain Monte Carlo simulation.     

Analyzing the dynamic system model with discrete failure time distribution

The present study deals with the method of estimation of the parameters of k-components load-sharing parallel system model in which each component’s failure time distribution is assumed to be geometric. The maximum likelihood estimates of the load-share parameters with their standard errors are obtained. (1 − γ) 100% joint, Bonferroni simultaneous and two bootstrap confidence intervals for the parameters have been constructed. Further, recognizing the fact that life testing experiments are time consuming, it seems realistic to consider the load-share parameters to be random variable. Therefore, Bayes estimates along with their standard errors of the parameters are obtained by assuming Jeffrey’s invariant and gamma priors for the unknown parameters. Since, Bayes estimators can not be found in closed form expressions, Tierney and Kadane’s approximation method have been used to compute Bayes estimates and standard errors of the parameters. Markov Chain Monte Carlo technique such as Gibbs sampler is also used to obtain Bayes estimates and highest posterior density credible intervals of the load-share parameters. Metropolis–Hastings algorithm is used to generate samples from the posterior distributions of the unknown parameters.     

A new nonparametric bivariate test for two sample location problem

A strictly nonparametric bivariate test for two sample location problem is proposed. The proposed test is easy to apply and does not require the stringent condition of affine-symmetry or elliptical symmetry which is required by some of the major tests available for the same problem. The power function of the proposed test is calculated. The asymptotic distribution of the proposed test statistic is found to be normal. The power of proposed test is compared with some of the well-known tests under various distributions using Monte Carlo simulation technique. The power study shows that the proposed test statistic performs better than most of the test statistics for almost all the distributions considered here. As soon as the underlying population structure deviates from normality, the ability of the proposed test statistic to detect the smallest shift in location increases as compared to its competitors. The application of the test is shown by using a data set.     

Reports of Conferences,Institutes, and Seminars

This installment of "Serials Spoken Here" covers events that transpired between late September and late October 2008. Reported herein are two Webinars, one on ONIX for Serials, the other on SUSHI, and two conferences: the eighty-fourth annual Meeting of the Potomac Technical Processing Librarians and the New England Library Association's Annual Conference.     

Cumulative correspondence analysis of ordered categorical data from industrial experiments

Most studies of quality improvement deal with ordered categorical data from industrial experiments. Accounting for the ordering of such data plays an important role in effectively determining the optimal factor level of combination. This paper utilizes the correspondence analysis to develop a procedure to improve the ordered categorical response in a multifactor state system based on Taguchi's statistic. Users may find the proposed procedure in this paper to be attractive because we suggest a simple and also popular statistical tool for graphically identifying the really important factors and determining the levels to improve process quality. A case study for optimizing the polysilicon deposition process in a very large-scale integrated circuit is provided to demonstrate the effectiveness of the proposed procedure.     

Finite normal mixture copulas for multivariate discrete data modeling

A new family of copulas is introduced that provides flexible dependence structure while being tractable and simple to use for multivariate discrete data modeling. The construction exploits finite mixtures of uncorrelated normal distributions. Accordingly, the cumulative distribution function is simply the product of univariate normal distributions. At the same time, however, the mixing operation introduces association. The properties of the new family of copulas are examined and a concrete application is used to show its applicability.