The racialized patterns of police violence: The critical importance of research as praxis

The tragic killing of George Floyd at the hands of the police resulted in hundreds of thousands of protestors marching in the streets demanding change. The call for change criticized the killing of Blacks by law enforcement and challenged White supremacy as an institution of social control and racial violence. A key component of the marches and protests was a message to the residents of the United States: “Black Lives Matter.” As society grapples with a reckoning, researchers studying police violence for the past 6 decades have been empirically and theoretically debating the reasons why use of force by law enforcement continues to have a higher proportion of Black and Brown victims compared to Whites. Although the research on fatal police killings was studied by only a small number of individuals prior to 2014, after the killing of Michael Brown in Ferguson, Missouri the research in different areas of the country increased rapidly as did the forms of analysis and research disciplines making their own contributions. The Washington Post and Guardian news agencies established that deaths at the hands of the police were occurring for at least 900 to 1100 individual deaths per year for which firearms resulted in the greatest cause of death. As US government agencies failed to produce a national data source on police involved killings, the media took a leading role in providing greater national understanding. The authors examine what role academic researchers contribute to the discussion for solutions, particularly those from marginalized backgrounds. As protestors march, lawyers sue and defend, and politicians create new forms of legislation, researchers need to play a more important role initiating critical studies, making sense of the data, and providing a theoretical framework for which police violence can be understood. This article will provide an overview of the literature on racialized police violence, point out key patterns involving racial and ethnic disparities, and emphasize how researchers can play a more important role in advocating for change.     

Self-exciting threshold models for time series of counts with a finite range

In this article, an integer-valued self-exciting threshold model with a finite range based on the binomial INARCH(1) model is proposed. Important stochastic properties are derived, and approaches for parameter estimation are discussed. A real-data example about the regional spread of public drunkenness in Pittsburgh demonstrates the applicability of the new model in comparison to existing models. Feasible modifications of the model are presented, which are designed to handle special features such as zero-inflation.     

Attention and Executive Functions as Mediators of Attachment and Behavior Problems

The purpose of this study was to provide a more comprehensive understanding of the relation between early parent‐child interactions and subsequent behavior problems and how certain cognitive processes mediate this relation. Specifically, this study investigated whether attention, inhibition, and planning skills mediate the relation between attachment security and behavior problems. Data were collected as part of the National Institute of Child Health and Development‐Study of Early Child Care and Youth Development when children (N = 1004) were between 36 months and the third grade. Results from structural equation models indicated that sustained attention mediated the relation between disorganized attachment and social problems. Planning mediated the relation between disorganized attachment and subsequent thought problems, attention problems, and delinquent behavior. Avoidant, ambivalent, and disorganized attachment directly predicted several behavior problems. Implications for theory and future research are discussed.     

Control Chart for Monitoring Autocorrelated Process with Multiple Exogenous Inputs

We propose to use AR-Sieve Bootstrap in the construction of a control chart of an autocorrelated process influenced by multiple exogenous inputs. The control charts are compared with Exponentially Weighted Moving Average (EWMA) control chart through a simulation study. AR-Sieve bootstrap control limits are narrower than EWMA control limits. While the proposed method yields a higher rate of false alarms, it is quick in detecting even minimal structural changes.     

The Mediating Role of Emotion Dysregulation in the Relation Between Adult Attachment Insecurity and Depression Among Young Gay and Bisexual Men

Objectives: Attachment insecurity may be more pronounced among young gay and bisexual men (YGBM). Further, attachment insecurity is associated with dysregulated patterns of emotion regulation, which can lead to depression. However, pathways linking attachment insecurity to depression are underexplored among YGBM. Methods: This study used pilot data from N?=?67 YGBM to examine if emotion dysregulation mediated the association between attachment insecurity and depression. Results: Results supported the study hypotheses. Attachment insecurity was associated with emotion dysregulation, which was associated with depression. Conclusion: Findings provide preliminary evidence that emotion regulation training may be a useful approach for addressing depression among YGBM.     

Optimal acceptance sampling for modules F and F1 of the European Measuring Instruments Directive

ABSTRACT

Acceptance sampling plans offered by ISO 2859-1 are far from optimal under the conditions for statistical verification in modules F and F1 as prescribed by Annex II of the Measuring Instruments Directive (MID) 2014/32/EU, resulting in sample sizes that are larger than necessary. An optimised single-sampling scheme is derived, both for large lots using the binomial distribution and for finite-sized lots using the exact hypergeometric distribution, resulting in smaller sample sizes that are economically more efficient while offering the full statistical protection required by the MID.     

Sequential Monte Carlo for rare event estimation

This paper discusses a novel strategy for simulating rare events and an associated Monte Carlo estimation of tail probabilities. Our method uses a system of interacting particles and exploits a Feynman-Kac representation of that system to analyze their fluctuations. Our precise analysis of the variance of a standard multilevel splitting algorithm reveals an opportunity for improvement. This leads to a novel method that relies on adaptive levels and produces, in the limit of an idealized version of the algorithm, estimates with optimal variance. The motivation for this theoretical work comes from problems occurring in watermarking and fingerprinting of digital contents, which represents a new field of applications of rare event simulation techniques. Some numerical results show performance close to the idealized version of our technique for these practical applications.     

Survival and lifetime data analysis with a flexible class of distributions

We introduce a general class of continuous univariate distributions with positive support obtained by transforming the class of two-piece distributions. We show that this class of distributions is very flexible, easy to implement, and contains members that can capture different tail behaviours and shapes, producing also a variety of hazard functions. The proposed distributions represent a flexible alternative to the classical choices such as the log-normal, Gamma, and Weibull distributions. We investigate empirically the inferential properties of the proposed models through an extensive simulation study. We present some applications using real data in the contexts of time-to-event and accelerated failure time models. In the second kind of applications, we explore the use of these models in the estimation of the distribution of the individual remaining life.