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.

The effect of number of siblings on adult mortality: Evidence from Swedish registers for cohorts born between 1938 and 1972

Demographic research has paid much attention to the impact of childhood conditions on adult mortality. We focus on one of the key aspects of early life conditions, sibling group size, and examine the causal effect of growing up in a large family on mortality. While previous studies have focused on low- or middle-income countries, we examine whether growing up in a large family is a disadvantage in Sweden, a context where most parents have adequate resources, which are complemented by a generous welfare state. We used Swedish register data and frailty models, examining all-cause and cause-specific mortality between the ages of 40 and 74 for the 1938–72 cohorts, and also a quasi-experimental approach that exploited multiple births as a source of exogenous variation in the number of siblings. Overall our results do not indicate that growing up in a large family has a detrimental effect on longevity in Sweden.     

Poking a sleeping bear: the challenge of organizational recruitment for controversial topics

ABSTRACT

Researchers often approach employers to investigate employees’ work and family experiences. Organizational willingness to grant access to employees can vary, especially when the research topic is seen as controversial or contentious for the employer. This paper explores this methodological challenge using a research example from Manitoba, Canada, which explored the use of parental leave by male employees and the impact of managerial attitudes and corporate culture on usage. Sixty large employers were recruited with only seven of those organizations agreeing to participate. In this paper, the reasons organizations gave for declining to participate and the implications of their decisions for the research are examined. Although the final sample included 905 managers and employees, participating organizations tended to be employee-focused and family-friendly employers. Organizations declined participation for a variety of reasons: avoiding raising the issue with unions, awareness that their policies unfairly benefited female leave takers, and simply not seeing the relevance of a topic relating to men’s work–family experiences. A dialogue often absent from the literature, it is important to understand how employers can limit researchers’ access to employees on controversial topics. The existence of such barriers suggests alternative avenues to recruit participants directly when topics are contentious for employers.     

A note on the posterior inference for the Yule–Simon distribution

The Yule–Simon distribution has been out of the radar of the Bayesian community, so far. In this note, we propose an explicit Gibbs sampling scheme when a Gamma prior is chosen for the shape parameter. The performance of the algorithm is illustrated with simulation studies, including count data regression, and a real data application to text analysis. We compare our proposal to the frequentist counterparts showing better performance of our algorithm when a small sample size is considered.     

Approximate confidence intervals for the weighted kappa coefficient of a binary diagnostic test subject to a case–control design

Case–control design to assess the accuracy of a binary diagnostic test (BDT) is very frequent in clinical practice. This design consists of applying the diagnostic test to all of the individuals in a sample of those who have the disease and in another sample of those who do not have the disease. The sensitivity of the diagnostic test is estimated from the case sample and the specificity is estimated from the control sample. Another parameter which is used to assess the performance of a BDT is the weighted kappa coefficient. The weighted kappa coefficient depends on the sensitivity and specificity of the diagnostic test, on the disease prevalence and on the weighting index. In this article, confidence intervals are studied for the weighted kappa coefficient subject to a case–control design and a method is proposed to calculate the sample sizes to estimate this parameter. The results obtained were applied to a real example.     

A backward construction and simulation of correlated Poisson processes

In this paper, we consider a generalisation of the backward simulation method of Duch et al. [New approaches to operational risk modeling. IBM J Res Develop. 2014;58:1–9] to build bivariate Poisson processes with flexible time correlation structures, and to simulate the arrival times of the processes. The proposed backward construction approach uses the Marshall–Olkin bivariate binomial distribution for the conditional law and some well-known families of bivariate copulas for the joint success probability in lieu of the typical conditional independence assumption. The resulting bivariate Poisson process can exhibit various time correlation structures which are commonly observed in real data.     

On confidence intervals for the mean past lifetime function under random censorship

The mean past lifetime (MPL) function (also known as the expected inactivity time function) is of interest in many fields such as reliability theory and survival analysis, actuarial studies and forensic science. For estimation of the MPL function some procedures have been proposed in the literature. In this paper, we give a central limit theorem result for the estimator of MPL function based on a right-censored random sample from an unknown distribution. The limiting distribution is used to construct normal approximation-based confidence interval for MPL. Furthermore, we use the empirical likelihood ratio procedure to obtain confidence interval for the MPL function. These two intervals are compared with each other through simulation study in terms of coverage probability. Finally, a couple of numerical example illustrating the theory is also given.     

New goodness of fit tests for the Cauchy distribution

Some goodness-of-fit procedures for the Cauchy distribution are presented. The power comparisons indicate that the new tests possess good performances among the competitors, especially against symmetric alternatives. A financial data set is analyzed for illustration.     

Estimation of P{X < Y} for geometric—exponential model based on complete and censored samples

This article deals with the estimation of R = P{X < Y}, where X and Y are independent random variables from geometric and exponential distribution, respectively. For complete samples, the MLE of R, its asymptotic distribution, and confidence interval based on it are obtained. The procedure for deriving bootstrap-p confidence interval is presented. The UMVUE of R and UMVUE of its variance are derived. The Bayes estimator of R is investigated and its Lindley's approximation is obtained. A simulation study is performed in order to compare these estimators. Finally, all point estimators for right censored sample from the exponential distribution, are obtained.