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.     

Thank God you're here: the coming generation and their role in future‐proofing Australia from the challenges of population ageing

Like much of the industrialised world, Australia's population is ageing, the implications of which are twofold: increasing demand for publicly funded services and a decline in the supply of prime working‐age people. In grappling with the challenges of a diminishing workforce, the Australian Government is currently relying on its migration programs to provide both the much‐needed labour and skills for the resource boom and also to stimulate the economy through population growth. However, there may be another, not yet fully considered solution to the upcoming demographic problem. This paper investigates how the grandchildren of the baby boomers, termed here the Thank God You're Here generation (Gen TGYH), might impact on Australia's predicted workforce shortage. This generation of workers will enter the labour force as the last of the baby boomers reach retirement age, and will not only be bigger in size than preceding generations (Y, X and Baby Boomers), but also potentially be better educated than the retiring generation. This paper will also canvas the opportunities for both Gen TGYH and employers as well as the challenges for policymakers and governments in maximising the opportunity provided by this generation in the Australian economy.     

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.     

Do cultural orientations moderate the relation between Chinese adolescents’ shyness and depressive symptoms? It depends on their academic achievement

We examined the moderating roles of individualistic and collectivistic cultural orientations and academic achievement on the relation between Chinese adolescents’ shyness and depressive symptoms. A sample of Chinese adolescents (N = 492) from an urban school participated in the study during seventh (T1) and eighth (T2) grades. Adolescents self‐reported their shyness, cultural orientations, and depressive symptoms. The school provided records of their academic achievement. Concurrently, shyness and individualism were positively whereas collectivism and academic achievement were negatively, associated with adolescents’ depressive symptoms. Longitudinally, T1 shyness (but not individualism, collectivism, or academic achievement) predicted T2 depressive symptoms after controlling for stability in depressive symptoms. Concurrent relations between shyness and depressive symptoms were moderated by adolescents’ cultural orientations. Specifically, collectivism was protective whereas individualism was harmful, for shy adolescents’ adjustment. Furthermore, collectivism and academic achievement jointly moderated the relations between shyness and depressive symptoms concurrently and longitudinally. The results suggest that cultural orientations may influence shy adolescents’ depression symptoms through individual‐level self‐evaluation, and indicate that cultural factors and academic achievement need to be considered comprehensively for understanding and improving shy Chinese adolescents’ psychological adjustment.     

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)