The Discrepancy Between Two Approaches to Global Poverty: What Does it Reveal?

Social Indicators Research - For decades, international communities have developed poverty measures to inform needs assessment and aid allocation. Building on these efforts, this paper examines the...     

Joint impact of multiple observations on a subset of variables in multiple linear regression

In multiple linear regression analysis, each observation affects the fitted regression equation differently and has varying influences on the regression coefficients of the different variables. Chatterjee & Hadi (1988) have proposed some measures such as DSSE_ij (Impact on Residual Sum of Squares of simultaneously omitting the ith observation and the jth variable), F_j (Partial F-test for the jth variable) and F_j(i) (Partial F-test for the jth variable omitting the ith observation) to show the joint impact and the interrelationship that exists among a variable and an observation. In this paper we have proposed more extended form of those measures DSSE_IJ, F_J and F_J(I) to deal with the interrelationships that exist among the multiple observations and a subset of variables by monitoring the effects of the simultaneous omission of multiple variables and multiple observations.     

Religious Attendance,Stress, and Happiness in South Korea: Do Gender and Religious Affiliation Matter?

Is religious attendance positively associated with happiness in South Korea? If yes, can religious attendance buffer against the harmful effect of stress on happiness? Moreover, do gender and religious affiliation modify these associations? This study addresses these questions with data from 2009 Korean General Social Survey which is a nationally representative survey (N = 1,599). Ordinal least square regression analyses reveal that although the effect size is relatively small, religious attendance is associated with a higher level of happiness in South Korea. However, this positive effect holds only for women and only for Protestants. In addition, an interaction effect between religious attendance and stress is observed for women only; the negative association between stress and happiness is weakened among those women who report more frequent church attendance. In this regard, a high level of church attendance buffers against the deleterious effects of stress on happiness for women. I discuss the implications of the findings with regard to theories about religion, mental health, and gender in South Korean context.     

Development of predictive signatures for treatment selection in precision medicine with survival outcomes

For survival endpoints in subgroup selection, a score conversion model is often used to convert the set of biomarkers for each patient into a univariate score and using the median of the univariate scores to divide the patients into biomarker‐positive and biomarker‐negative subgroups. However, this may lead to bias in patient subgroup identification regarding the 2 issues: (1) treatment is equally effective for all patients and/or there is no subgroup difference; (2) the median value of the univariate scores as a cutoff may be inappropriate if the sizes of the 2 subgroups are differ substantially. We utilize a univariate composite score method to convert the set of patient's candidate biomarkers to a univariate response score. We propose applying the likelihood ratio test (LRT) to assess homogeneity of the sampled patients to address the first issue. In the context of identification of the subgroup of responders in adaptive design to demonstrate improvement of treatment efficacy (adaptive power), we suggest that subgroup selection is carried out if the LRT is significant. For the second issue, we utilize a likelihood‐based change‐point algorithm to find an optimal cutoff. Our simulation study shows that type I error generally is controlled, while the overall adaptive power to detect treatment effects sacrifices approximately 4.5% for the simulation designs considered by performing the LRT; furthermore, the change‐point algorithm outperforms the median cutoff considerably when the subgroup sizes differ substantially.     

Mixtures of regression models with incomplete and noisy data

The estimation of the mixtures of regression models is usually based on the normal assumption of components and maximum likelihood estimation of the normal components is sensitive to noise, outliers, or high-leverage points. Missing values are inevitable in many situations and parameter estimates could be biased if the missing values are not handled properly. In this article, we propose the mixtures of regression models for contaminated incomplete heterogeneous data. The proposed models provide robust estimates of regression coefficients varying across latent subgroups even under the presence of missing values. The methodology is illustrated through simulation studies and a real data analysis.     

Small‐sphere distributions for directional data with application to medical imaging

We propose novel parametric concentric multi‐unimodal small‐subsphere families of densities for p ? 1 ≥ 2‐dimensional spherical data. Their parameters describe a common axis for K small hypersubspheres, an array of K directional modes, one mode for each subsphere, and K pairs of concentrations parameters, each pair governing horizontal (within the subsphere) and vertical (orthogonal to the subsphere) concentrations. We introduce two kinds of distributions. In its one‐subsphere version, the first kind coincides with a special case of the Fisher–Bingham distribution, and the second kind is a novel adaption that models independent horizontal and vertical variations. In its multisubsphere version, the second kind allows for a correlation of horizontal variation over different subspheres. In medical imaging, the situation of p ? 1 = 2 occurs precisely in modeling the variation of a skeletally represented organ shape due to rotation, twisting, and bending. For both kinds, we provide new computationally feasible algorithms for simulation and estimation and propose several tests. To the best knowledge of the authors, our proposed models are the first to treat the variation of directional data along several concentric small hypersubspheres, concentrated near modes on each subsphere, let alone horizontal dependence. Using several simulations, we show that our methods are more powerful than a recent nonparametric method and ad hoc methods. Using data from medical imaging, we demonstrate the advantage of our method and infer on the dominating axis of rotation of the human knee joint at different walking phases.     

SODA WARS: THE EFFECT OF A SODA TAX ELECTION ON UNIVERSITY BEVERAGE SALES

We examine how soda sales changed due to the campaign attention and election outcome of a local excise tax on sugar‐sweetened beverages. Using panel data of beverage sales from university retailers in Berkeley, California, we estimate that soda purchases relative to control beverages significantly dropped immediately after the election, months before the tax was implemented in the city of Berkeley or on campus. Supplemental scanner data from off‐campus retailers reveal this result is not unique to the university setting. Our findings suggest soda tax media coverage and election outcomes can have larger effects on purchasing behavior than the tax itself. (JEL D12, H20, C23, I38, Q18)     

Family Roles as Moderators of the Relationship Between Schedule Flexibility and Stress

Employer initiatives that address the spillover of work strain onto family life include flexible work schedules. This study explored the mediating role of negative work–family spillover in the relationship between schedule flexibility and employee stress and the moderating roles of gender, family workload, and single‐parent status. Data were drawn from the 2008 National Study of the Changing Workforce, a nationally representative sample of working adults (N = 2,769). The results indicated that schedule flexibility was associated with less employee stress and that these associations were mediated by perceptions of negative work–family spillover. This study found the moderating relationships of gender, family workload, and single parenting in the relationships between schedule flexibility and negative work–family spillover and stress. Schedule flexibility had stronger relationships in reducing negative work–family spillover and stress among women, single parents, and employees with heavier family workloads. The findings provide empirical support for intervention efforts involving schedule flexibility to reduce workplace stress among employees with family responsibilities.     

A reference activity model for smart factory design and improvement

Smart manufacturing systems (SMSs) are envisioned to contain highly automated and IT-driven production systems. To address the complexity that arises in such systems, a standard and holistic model for describing its activities and their interrelationships is needed. This paper introduces a factory design and improvement (FDI) activity model and illustrates a case study of FDI in an electromechanical component factory. In essence, FDI is a reference activity model that encompasses a range of manufacturing system activities for designing and improving a factory during its initial development and also its operational phases. The FDI model shows not only the dependency between activities and manufacturing control levels but also the pieces of information and software functions each activity relies on. We envision that the availability of these pieces of information in digital form to integrate across the software functions will increase the agility of factory design and improvement projects. Therefore, our future work lies in contributing to standards for exchanging such information.