Improving the detection of unusual observations in high‐dimensional settings

Multivariate control charts are used to monitor stochastic processes for changes and unusual observations. Hotelling's T² statistic is calculated for each new observation and an out‐of‐control signal is issued if it goes beyond the control limits. However, this classical approach becomes unreliable as the number of variables p approaches the number of observations n, and impossible when p exceeds n. In this paper, we devise an improvement to the monitoring procedure in high‐dimensional settings. We regularise the covariance matrix to estimate the baseline parameter and incorporate a leave‐one‐out re‐sampling approach to estimate the empirical distribution of future observations. An extensive simulation study demonstrates that the new method outperforms the classical Hotelling T² approach in power, and maintains appropriate false positive rates. We demonstrate the utility of the method using a set of quality control samples collected to monitor a gas chromatography–mass spectrometry apparatus over a period of 67 days.     

Challenging the Myths of Black Women—A Short-Term,Structured, Art Experience Group: Exploring the Intersections of Race,Gender, and Intergenerational Trauma

ABSTRACT

The authors describe a short-term structured group process for African American women in the suburbs of Washington, DC, highlighting the perspective of the group leaders. The group was started to address the unique needs of African American women who are also survivors of childhood abuse and neglect. The group leaders used discussion and art in the group to explore the intersections of race, gender, and intergenerational trauma. Having shared experiences with the participants of the group, the authors explore the ways the group leaders were changed and challenged in the process.     

Bayesian credible intervals for response surface optima

In response surface methodology, one is usually interested in estimating the optimal conditions based on a small number of experimental runs which are designed to optimally sample the experimental space. Typically, regression models are constructed from the experimental data and interrogated in order to provide a point estimate of the independent variable settings predicted to optimize the response. Unfortunately, these point estimates are rarely accompanied with uncertainty intervals. Though classical frequentist confidence intervals can be constructed for unconstrained quadratic models, higher order, constrained or nonlinear models are often encountered in practice. Existing techniques for constructing uncertainty estimates in such situations have not been implemented widely, due in part to the need to set adjustable parameters or because of limited or difficult applicability to constrained or nonlinear problems. To address these limitations a Bayesian method of determining credible intervals for response surface optima was developed. The approach shows good coverage probabilities on two test problems, is straightforward to implement and is readily applicable to the kind of constrained and/or nonlinear problems that frequently appear in practice.     

Empirical Prediction Intervals for County Population Forecasts

Population forecasts entail a significant amount of uncertainty, especially for long-range horizons and for places with small or rapidly changing populations. This uncertainty can be dealt with by presenting a range of projections or by developing statistical prediction intervals. The latter can be based on models that incorporate the stochastic nature of the forecasting process, on empirical analyses of past forecast errors, or on a combination of the two. In this article, we develop and test prediction intervals based on empirical analyses of past forecast errors for counties in the United States. Using decennial census data from 1900 to 2000, we apply trend extrapolation techniques to develop a set of county population forecasts; calculate forecast errors by comparing forecasts to subsequent census counts; and use the distribution of errors to construct empirical prediction intervals. We find that empirically-based prediction intervals provide reasonably accurate predictions of the precision of population forecasts, but provide little guidance regarding their tendency to be too high or too low. We believe the construction of empirically-based prediction intervals will help users of small-area population forecasts measure and evaluate the uncertainty inherent in population forecasts and plan more effectively for the future.     

“Men never cry”: Teaching Mormon Manhood in the Church of Jesus Christ of Latter-day Saints

We examine the ways Mormon leaders establish “what it means to be a man” for their followers. Based on content analysis of over 40 years of archival material, we analyze how Mormon leaders represent manhood as the ability to signify control over self and others as well as an inability to be controlled. Specifically, we demonstrate how these representations stress controlling the self, emotional and sexual expression, and others while emphasizing the development of self-reliance and independence from others’ control. We draw out implications for understanding (1) how religious leaders create ideal notions of manhood, (2) what the religious interpretations of secular constructions of manhood are, and (3) how these relate to the reproduction of gender inequalities.     

Best Practice to Order Authors in Multi/Interdisciplinary Health Sciences Research Publications

Misunderstanding and disputes about authorship are commonplace among members of multi/interdisciplinary health research teams. If left unmanaged and unresolved, these conflicts can undermine knowledge sharing and collaboration, obscure accountability for research, and contribute to the incorrect attribution of credit. To mitigate these issues, certain researchers suggest quantitative authorship distributions schemes (e.g., point systems), while others wish to replace or minimize the importance of authorship by using “contributorship”—a system based on authors’ self-reporting contributions. While both methods have advantages, we argue that authorship and contributorship will most likely continue to coexist for multiple ethical and practical reasons. In this article, we develop a five-step “best practice” that incorporates the distribution of both contributorship and authorship for multi/interdisciplinary research. This procedure involves continuous dialogue and the use of a detailed contributorship taxonomy ending with a declaration explaining contributorship, which is used to justify authorship order. Institutions can introduce this approach in responsible conduct of research training as it promotes greater fairness, trust, and collegiality among team members and ultimately reduces confusion and facilitates resolution of time-consuming disagreements.     

Fertility after natural disaster: Hurricane Mitch in Nicaragua

This investigation evaluates the effect of Hurricane Mitch on women’s reproductive outcomes throughout Nicaragua. This research aim is achieved by analyzing a unique Nicaraguan Living Standards Measurement Study panel dataset that tracks women’s fertility immediately before and at two time points after Hurricane Mitch, combined with satellite-derived municipality-level precipitation data for the 10-day storm period. Results show higher odds of post-disaster fertility in municipalities receiving higher precipitation levels in the immediate post-Hurricane Mitch period. However, fertility normalizes between disaster and non-disaster areas 4 to 6 years after the storm. These findings suggest that the disruptive effects of a natural disaster such as Hurricane Mitch can have an initial stimulative effect on fertility but that effect is ephemeral.     

Stress,strain, coping and social support for affected family members attending the National Problem Gambling Clinic,London

Aims were: to compare burden experienced by affected family members (AFMs) attending a problem gambling treatment clinic in London, England with that of AFMs affected by substance problems; to examine socio-demographic correlates of AFM burden; to evaluate change following an intervention designed for AFMs; and to test the assumption of the stress-strain-coping-support (SSCS) model that change in AFM coping is important. AFMs (N = 215) completed a gambling version of the short questionnaire for family members affected by addiction (SQFM-AA) which assesses stressful impact, symptoms of ill health, ways of coping, social support and overall burden. All received a 5-Step Method workbook, based on the SSCS model. The SQFM-AA was repeated three to six months later (n = 96). T-test analyses showed that baseline burden and related variables were comparable to those of family members affected by substance problems, were greater for wives and those living in the same household as the gambling relative, and were significantly reduced at follow-up. Regression modelling indicated the importance, for AFMs’ health, of reduced levels of engaged-emotional coping. Family members affected by gambling, some subgroups especially, experience high levels of burden. They can benefit from a model-based intervention, and coping change may be an important process.     

Kinship care and issues in permanency planning

Kinship caregivers are a child-care resource for families experiencing stress or temporary parenting due to illness, incarceration, or death of a parent. This article examines whether and how felt caregiver burden influences the reported propensity of caregivers to want to adopt the children in their care. Kinship caregivers who were enrolled in KinNET completed the survey (N = 102) and the data were entered anonymously into SPSS for analysis. Their mean age was 57.51 years (SD = 10.13), 95% were female (SD = .19), and two-thirds were non-white (SD = .73). Using “likelihood of adopting the child in my care,” as the outcome variable in the linear regression analysis, caregiver’s age, monthly income, and total hours employed were significant predictors. Total pressures, family service needs, and physical problems scales were not statistically significant predictors. The adjusted R square was .439 and significant (.006). Understanding the factors that are predictive of adopting children in kinship care will help programs target services more effectively. Helping kinship caregivers and the children in their care is also important in promoting their health and social well-being.     

“Friendly” Initiatives: An Emerging Approach to Improve Communities for Vulnerable Populations

A growing number of cities and towns are implementing “friendly” initiatives to change the community’s social and physical infrastructure to address the needs of a particular vulnerable segment of their population. Three prominent examples are aging-friendly, child-friendly, and immigrant-friendly initiatives. Although the limited but growing literature describes these initiatives as promising strategies to improve the quality of life of the targeted population, to date there has been little written about the underlying goals, values, and assumptions of these efforts. Using the value-critical approach, this article aims to better understand these aspects of population-friendly initiatives by examining the scholarly and grey literature. Social workers engaged in community and policy practice can play a key role in these efforts and call attention to the ways they may alleviate or exacerbate inequities. Future research is needed to assess the effects of these initiatives on their targeted population as well as other community residents.