Dynamic version of weighted cumulative residual entropy

Some extensions of Shannon entropy to the survival function have been recently proposed. Misagh et al. (2011 Misagh, F., Panahi, Y., Yari, G.H., Shahi, R. (2011, September). Weighted cumulative entropy and its estimation. In: Quality and Reliability (ICQR), 2011, IEEE International conference (pp. 477–480), IEEE.[Crossref] , [Google Scholar]) introduced weighted cumulative residual entropy (WCRE) that was studied more by Mirali et al. (2015 Mirali, M., Baratpour, S., Fakoor, V. (2015). On weighted cumulative residual entropy. Commun. Stat. Theory Methods. doi:10.1080103610926.2015.1053932.[Web of Science ®] , [Google Scholar]). In this article, the dynamic version of WCRE is proposed. Some relationships of this measure with well-known reliability measures and ageing classes are studied and some characterization results for exponential and Rayleigh distributions are provided. Also, a non parametric estimation of dynamic version of WCRE is introduced and its asymptotic behavior is investigated.     

Bayesian quantile regression for skew-normal linear mixed models

Linear mixed models have been widely used to analyze repeated measures data which arise in many studies. In most applications, it is assumed that both the random effects and the within-subjects errors are normally distributed. This can be extremely restrictive, obscuring important features of within-and among-subject variations. Here, quantile regression in the Bayesian framework for the linear mixed models is described to carry out the robust inferences. We also relax the normality assumption for the random effects by using a multivariate skew-normal distribution, which includes the normal ones as a special case and provides robust estimation in the linear mixed models. For posterior inference, we propose a Gibbs sampling algorithm based on a mixture representation of the asymmetric Laplace distribution and multivariate skew-normal distribution. The procedures are demonstrated by both simulated and real data examples.     

<Emphasis Type="BoldItalic">MAD-STEC</Emphasis>: a method for multiple automatic detection of space-time emerging clusters

Crime or disease surveillance commonly rely in space-time clustering methods to identify emerging patterns. The goal is to detect spatial-temporal clusters as soon as possible after its occurrence and to control the rate of false alarms. With this in mind, a spatio-temporal multiple cluster detection method was developed as an extension of a previous proposal based on a spatial version of the Shiryaev–Roberts statistic. Besides the capability of multiple cluster detection, the method have less input parameter than the previous proposal making its use more intuitive to practitioners. To evaluate the new methodology a simulation study is performed in several scenarios and enlighten many advantages of the proposed method. Finally, we present a case study to a crime data-set in Belo Horizonte, Brazil.     

$$D_s$$-optimality in copula models

Optimum experimental design theory has recently been extended for parameter estimation in copula models. The use of these models allows one to gain in flexibility by considering the model parameter set split into marginal and dependence parameters. However, this separation also leads to the natural issue of estimating only a subset of all model parameters. In this work, we treat this problem with the application of the \(D_s\)-optimality to copula models. First, we provide an extension of the corresponding equivalence theory. Then, we analyze a wide range of flexible copula models to highlight the usefulness of \(D_s\)-optimality in many possible scenarios. Finally, we discuss how the usage of the introduced design criterion also relates to the more general issue of copula selection and optimal design for model discrimination.     

Increasing Competency,Self-Confidence,and Connectedness Among Foster Care Alumni Entering a 4-Year University: Findings from an Early-Start Program

Research shows that few foster care alumni enroll and complete post-secondary education. For those who do enroll, many experience challenges associated with academic and social adjustment and are at risk of dropping out. Many college-based programs are being developed and are available to foster care alumni to support them during their post-secondary education. This study used pre-tests, post-tests, and journal entries of seventeen participants to evaluate a strengths-based, resilience-oriented early-start program for newly enrolled students at a large public university that provides knowledge about the institution, resources (e.g., tutoring), and social support necessary for foster care alumni to make a smooth transition into college life and to increase short and long-term student success. Quantitative and qualitative findings indicate that students who participated in the early-start program showed increased confidence and competency in academic and social adjustment. Findings also showed personal growth (e.g., building resiliency) and an increased connectedness among students who participated in the program. Study findings can inform the development of new on-campus support programs and help enhance existing programming. Future research should address short and long-term outcomes and experiences of students who are former foster youth who have participated in on-campus support programs.     

Alone and adrift: The association between mass school shootings,school size,and student support

Background

School shootings have approached epidemic levels in recent years. While mental illness is undoubtedly involved in nearly all cases of mass school violence, we sought to determine how environmental context may exacerbate preexisting personal factors. The present study investigated the associations between mass school shootings, school enrollment size, student–teacher ratios, and student transitions.

Both Whistleblowers and the Scientists They Accuse Are Vulnerable and Deserve Protection

Whistleblowers play an important role diagnosing research misconduct, but often experience severe negative consequences. That is also true for incorrectly accused scientists. Both categories are vulnerable and deserve protection. Whistleblowers must proceed carefully and cautiously. Anonymous whistleblowing should be discouraged but cannot be ignored when the allegations are specific, serious, and plausible. When accused of a breach of research integrity it is important to be as transparent as possible. Sometimes accusations are false in the sense that the accuser knows or should know that the allegations are untrue. A mala fide whistleblower typically does not act carefully and we postulate a typology that may help in detecting them. Striking the right balance between whistleblower protection and timely unmasking false and identifying incorrect accusations is a tough dilemma leaders of research institutions have to face.     

Minimal Risk in Pediatric Research: A Philosophical Review and Reconsideration

Despite more than thirty years of debate, disagreement persists among research ethicists about the most appropriate way to interpret the U.S. regulations on pediatric research, specifically the categories of “minimal risk” and a “minor increase over minimal risk.” Focusing primarily on the definition of “minimal risk,” we argue in this article that the continued debate about the pediatric risk categories is at least partly because their conceptual status is seldom considered directly. Once this is done, it becomes clear that the most popular strategy for interpreting “minimal risk”—defining it as a specific set of risks—is indefensible and, from a pragmatic perspective, unlikely to resolve disagreement. Primarily this is because judgments about minimal risk are both normative and heavily intuitive in nature and thus cannot easily be captured by reductions to a given set of risks. We suggest instead that a more defensible approach to evaluating risk should incorporate room for reflection and deliberation. This dispositional, deliberative framework can nonetheless accommodate a number of intellectual resources for reducing reliance on sheer intuition and improving the quality of risk evaluations.