Values and happiness among Asian adolescents: a cross-national study

Despite policy efforts to increase adolescent happiness, their impact has been unsatisfactory. Their limited impact may be rooted from a discrepancy between values that adolescents pursued and those that the policies were based on. To provide policy implications, our study aims to identify prevailing values for South Korean, Japanese, and Chinese adolescents and to examine the relationship between the values and self-rated happiness (SRH). A cross-sectional study was conducted using survey data collected on approximately 2000 middle and high school students (7th to 12th school grade) from each country in 2008. Firstly, an explanatory factor analysis was conducted to identify salient adolescent values from each country. Subsequently, a multiple logistic regression analysis was conducted for each population group to examine the relationship between the identified values and adolescent SRH after controlling for sociodemographic characteristics. We found that benevolence and altruism were positively associated with adolescent SRH in all three population groups. Patriarchy was associated with SRH positively in Chinese yet inversely in Japanese. Success pursuit was inversely associated with SRH in Korean. Policy efforts based on values of communities or social harmony may benefit adolescents’ SRH in these three countries.     

Leadership research and cognitive neuroscience: The state of this union

Advances in cognitive neuroscience and other approaches to understanding human behavior from a biological standpoint are only now beginning to filter into leadership research. The purpose of this introduction to the Leadership Quarterly Special Issue on the Biology of Leadership is to outline the organizational cognitive neuroscience approach to leadership research, and show how such an approach can fruitfully inform both leadership and neuroscientific research. Indeed, we advance the view that the further application of cognitive neuroscientific techniques to leadership research will pay great dividends in our understanding of effective leadership behaviors and as such, a future symbiosis between the two fields is a necessity.     

Decomposition of Changes in Korean Wage Inequality, 1998–2007

South Korea experienced a steep increase in wage inequality between the Asian financial crisis in 1997 and the global financial crisis in 2008. This paper investigates the causes of the sharp change during that time period by looking at the contributions of changes in the distributions of schooling and unionization. The effects are estimated applying two robust distributional function based decomposition methods on Korean Labor and Panel Survey data for the time period 1998–2007. The results suggest changes in the distribution of schooling can explain about 10 % of the changes in the 90/50 percentile wage gap. The declining unionization rate does not have much impact on the upward trend of Korean wage inequality. In addition, aggregate decomposition results suggest that changes in labor force composition can explain a significant proportion of the total wage changes in the upper-tail of the distribution. Based on our findings we provide a list of policy recommendations to address the wage inequality issue in Korea.     

Data envelopment analysis in the presence of measurement error: case study from the National Database of Nursing Quality Indicators® (NDNQI®)

Data envelopment analysis (DEA) is the most commonly used approach for evaluating healthcare efficiency [B. Hollingsworth, The measurement of efficiency and productivity of health care delivery. Health Economics 17(10) (2008), pp. 1107–1128], but a long-standing concern is that DEA assumes that data are measured without error. This is quite unlikely, and DEA and other efficiency analysis techniques may yield biased efficiency estimates if it is not realized [B.J. Gajewski, R. Lee, M. Bott, U. Piamjariyakul, and R.L. Taunton, On estimating the distribution of data envelopment analysis efficiency scores: an application to nursing homes’ care planning process. Journal of Applied Statistics 36(9) (2009), pp. 933–944; J. Ruggiero, Data envelopment analysis with stochastic data. Journal of the Operational Research Society 55 (2004), pp. 1008–1012]. We propose to address measurement error systematically using a Bayesian method (Bayesian DEA). We will apply Bayesian DEA to data from the National Database of Nursing Quality Indicators^® to estimate nursing units’ efficiency. Several external reliability studies inform the posterior distribution of the measurement error on the DEA variables. We will discuss the case of generalizing the approach to situations where an external reliability study is not feasible.     

Objective Bayesian inference for the ratio of the scale parameters of two Weibull distributions

The Weibull distribution is widely used due to its versatility and relative simplicity. In our paper, the non informative priors for the ratio of the scale parameters of two Weibull models are provided. The asymptotic matching of coverage probabilities of Bayesian credible intervals is considered, with the corresponding frequentist coverage probabilities. We developed the various priors for the ratio of two scale parameters using the following matching criteria: quantile matching, matching of distribution function, highest posterior density matching, and inversion of test statistics. One particular prior, which meets all the matching criteria, is found. Next, we derive the reference priors for groups of ordering. We see that all the reference priors satisfy a first-order matching criterion and that the one-at-a-time reference prior is a second-order matching prior. A simulation study is performed and an example given.     

Using clinical signs of neglect to identify elder neglect cases

Elder neglect is the one of the most pervasive forms of mistreatment, and often the only place outside of the individual’s residence to identify and assist neglected individuals is in a medical setting. However, elder neglect cases treated in hospitals do not present with a single diagnosis or clinical sign, but rather involve a complex constellation of clinical signs. Currently, there is a lack of comprehensive guidelines on which clinical signs to use in screening tools for neglect among patients treated in hospitals. Using the DELPHI method, a group of experts developed and tested a scale to be used as a pre-screener that conceptually could be integrated into electronic health record systems so that it could identify potential neglect cases in an automated manner. By applying the scale as a pre-screener for neglect, the tool would reduce the pool of at-risk patients who would benefit from in-depth screening for elder neglect by 95%.     

A new stratified three-stage unrelated randomized response model for estimating a rare sensitive attribute based on the Poisson distribution

This article suggests an efficient method of estimating a rare sensitive attribute which is assumed following Poisson distribution by using three-stage unrelated randomized response model instead of the Land et al. model (2011 Land, M., S. Singh, and S. A. Sedory. 2011. Estimation of a rare sensitive attribute using poisson distribution. Statistics 46 (3):351–60. doi:10.1080/02331888.2010.524300.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) when the population consists of some different sized clusters and clusters selected by probability proportional to size(:pps) sampling. A rare sensitive parameter is estimated by using pps sampling and equal probability two-stage sampling when the parameter of a rare unrelated attribute is assumed to be known and unknown.

We extend this method to the case of stratified population by applying stratified pps sampling and stratified equal probability two-stage sampling. An empirical study is carried out to show the efficiency of the two proposed methods when the parameter of a rare unrelated attribute is assumed to be known and unknown.     

Fitting competing risks data to bivariate Pareto models

This paper revisits two bivariate Pareto models for fitting competing risks data. The first model is the Frank copula model, and the second one is a bivariate Pareto model introduced by Sankaran and Nair (1993 Sankaran, P. G., and N. U. Nair. 1993. A bivariate Pareto model and its applications to reliability. Naval Research Logistics 40 (7):1013–1020. doi:10.1002/1520-6750(199312)40:7%3c1013::AID-NAV3220400711%3e3.0.CO;2-7.[Crossref], [Web of Science ®] , [Google Scholar]). We discuss the identifiability issues of these models and develop the maximum likelihood estimation procedures including their computational algorithms and model-diagnostic procedures. Simulations are conducted to examine the performance of the maximum likelihood estimation. Real data are analyzed for illustration.     

Identifying Changing Aviation Threat Environments Within an Adaptive Homeland Security Advisory System

A critical component of aviation security consists of screening passengers and baggage to protect airports and aircraft from terrorist threats. Advancements in screening device technology have increased the ability to detect these threats; however, specifying the operational configurations of these devices in response to changes in the threat environment can become difficult. This article proposes to use Fisher information as a statistical measure for detecting changes in the threat environment. The perceived risk of passengers, according to prescreening information and behavior analysis, is analyzed as the passengers sequentially enter the security checkpoint. The alarm responses from the devices used to detect threats are also analyzed to monitor significant changes in the frequency of threat items uncovered. The key results are that this information‐based measure can be used within the Homeland Security Advisory System to indicate changes in threat conditions in real time, and provide the flexibility of security screening detection devices to responsively and automatically adapt operational configurations to these changing threat conditions.