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.     

Social Cognitive Predictors of the Career Goals of Korean American Students

Limited empirical study of the career development of Asian Americans in general and Korean Americans in particular has been conducted. The authors present the results of a theory‐based exploration of the career goals of Korean American university students in which ethnic identity, self‐efficacy, outcome expectations, and career interests were used to predict goal intentions for science and nonscience careers. Outcome expectations and career interests predicted a moderate amount of variance in science career goal intentions and a moderate to large amount of variance in nonscience career goal intentions. Korean American students' career goal development seems similar to that of American college students.     

谈谈学分制下如何做好学生党建工作

全面推行学分制是高校教学改革的深化,是教育和教学改革的一个发展阶段.但由于学分制所带来的思想教育、学生党建等新情况、新问题,应值得所有教育者认真思考和研究的.本文围绕学分制实行后给学生党建工作带来的"四难"以及如何应对提出了一些理论和实践的思考.     

The relationship between open innovation,entrepreneurship, and introduction of new business models in Korean and Indonesian information technology enterprises

This case study sought to identify the relationships that can exist between open innovation, entrepreneurship, and the introduction of new business models at the enterprise level. Eleven Korean enterprises and five Indonesian enterprises were chosen, to obtain minimum research generality. While the number of enterprises is not great, it provides enough samples to determine the concrete relationships among these factors. The article starts by pointing out the general relationship between entrepreneurship, open innovation, and the introduction of a new business model. It examines two different contexts: the difference between the Seoul and Daegu regional innovation systems, and the difference between the Indonesian and Korean national innovation systems.     

Older Drivers Retiring From the Road: An Application of the Selection,Optimization, and Compensation Model

Purpose: This study uses the selection, optimization, and compensation (SOC) model to compare older adults who have given up driving, those who still drive, and those who drive less to identify differences in the three groups. Design and Methods: This cross-sectional study of 281 older adults is part of the Naturally Occurring Retirement Community Demonstration Project. Study participants completed interviews that included questions on demographics, health and functioning, mental health, social support, and current levels of engagement in activities including current driving status. Results: Data suggest that driving retirement is a process and that a substantial number of people are in the transitional stage, where they are less functional than those who still drive and more similar to those who have retired from the road. Implications: Given the similarity of those who drive less to those who have given up driving, front-line professionals and policy makers must work together to ease the transition to driving retirement for those without adequate ability to effectively compensate for their inability to continue to drive safely.     

Rank Tests for Matched Survival Data

In a clinical trial with the time to an event as the outcome of interest, we may randomize a number of matched subjects, such as litters, to different treatments. The number of treatments equals the number of subjects per litter, two in the case of twins. In this case, the survival times of matched subjects could be dependent. Although the standard rank tests, such as the logrank and Wilcoxon tests, for independent samples may be used to test the equality of marginal survival distributions, their standard error should be modified to accommodate the possible dependence of survival times between matched subjects. In this paper we propose a method of calculating the standard error of the rank tests for paired two-sample survival data. The method is naturally extended to that for K-sample tests under dependence.