Investigating a Longitudinal Trajectory of Child Obesity and Its Association with Child Maltreatment in South Korea

This study investigated the association between child maltreatment and body mass index (BMI) using data from four waves (wave 2 in 2011 through 5 in 2014) of the Korean Children & Youth Panel Survey collected by the South Korean National Youth Policy Institute. We employed a latent growth curve modeling approach to estimate an unobserved latent trajectory and to test the longitudinal effects of child abuse and neglect on BMI. Our results indicate that child abuse is significantly associated with BMI and children who report higher levels of abuse tend to have higher rates of increase in their BMI. This study addresses a gap in the literature by demonstrating that a parent's maltreatment of their child has a long‐term effect on the rate of change in their BMI over time.     

Longitudinal Effects of Economic Preparation and Social Activities on Life and Family Relationship Satisfaction among Retirees

This longitudinal study examined the long‐term effects of economic preparation and social activity on life and family relationship satisfaction among retirees, particularly baby boomers. Data was obtained from the 2009 and 2011 Korean Retirement & Income Panel Study. A fixed effects model was employed to estimate unobservable individual‐specific effects and to control for study participants’ individual characteristics. The results show that both economic preparation and social activities have long‐term effects on baby boomers’ life and family relationship satisfaction. This study reveals that multidimensional aspects of preparation increase the long‐term impact of life satisfaction for retirees.     

Institutional rules for framing healthcare policy issues in national,financial, and specialized newspapers

By considering the role of institutional rules for news making, this study examines news frames embedded in 1162 stories from national, financial, and specialized newspapers with respect to four healthcare policy issues: “the decrease in pharmaceutical prices,” “the comprehensive medical payment system,” “swine flu,” and “humidifier-related lung disease.” Conflict, economy, crisis, and policy execution are dominant frames in stories about the policy issues, and these four frames are also major frames used by the newspapers. This phenomenon is understood as “concentration of healthcare frames.” We conducted in-depth interviews with 19 news reporters to identify institutional rules that might influence the formation of news frames. In-depth interviews revealed that similar types of frames resulted from institutional rules (e.g., journalist’s autonomy, news value, newspaper’s mission statement, and characteristics of readers). The findings suggest that health journalists follow institutional rules that govern the creation of news frames. To provide diverse perspectives on healthcare policy issues, newspapers need to reconsider their institutional rules.     

Kernel Density Estimator From Ranked Set Samples

We study kernel density estimator from the ranked set samples (RSS). In the kernel density estimator, the selection of the bandwidth gives strong influence on the resulting estimate. In this article, we consider several different choices of the bandwidth and compare their asymptotic mean integrated square errors (MISE). We also propose a plug-in estimator of the bandwidth to minimize the asymptotic MISE. We numerically compare the MISE of the proposed kernel estimator (having the plug-in bandwidth estimator) to its simple random sampling counterpart. We further propose two estimators for a symmetric distribution, and show that they outperform in MISE all other estimators not considering symmetry. We finally apply the methods in this article to analyzing the tree height data from Platt et al. (1988 Platt, W.J., Evans, G.M., Rathbun, S.L. (1988). The population dynamics of long-lived conifer (Pinus plaustris) (1988). Amer. Natrualist 131:491–525.[Crossref], [Web of Science ®] , [Google Scholar]) and Chen et al. (2003 Chen, Z., Bai, Z., Sinha, B.K. (2003). Ranked Set Sampling: Theory and Applications. New York: Springer. [Google Scholar]).     

Bridge Estimation for Linear Regression Models with Mixing Properties

Penalized regression methods have for quite some time been a popular choice for addressing challenges in high dimensional data analysis. Despite their popularity, their application to time series data has been limited. This paper concerns bridge penalized methods in a linear regression time series model. We first prove consistency, sparsity and asymptotic normality of bridge estimators under a general mixing model. Next, as a special case of mixing errors, we consider bridge regression with autoregressive and moving average (ARMA) error models and develop a computational algorithm that can simultaneously select important predictors and the orders of ARMA models. Simulated and real data examples demonstrate the effective performance of the proposed algorithm and the improvement over ordinary bridge regression.     

Semiparametric Bayesian hierarchical models for heterogeneous population in nonlinear mixed effect model: application to gastric emptying studies

Gastric emptying studies are frequently used in medical research, both human and animal, when evaluating the effectiveness and determining the unintended side-effects of new and existing medications, diets, and procedures or interventions. It is essential that gastric emptying data be appropriately summarized before making comparisons between study groups of interest and to allow study the comparisons. Since gastric emptying data have a nonlinear emptying curve and are longitudinal data, nonlinear mixed effect (NLME) models can accommodate both the variation among measurements within individuals and the individual-to-individual variation. However, the NLME model requires strong assumptions that are often not satisfied in real applications that involve a relatively small number of subjects, have heterogeneous measurement errors, or have large variation among subjects. Therefore, we propose three semiparametric Bayesian NLMEs constructed with Dirichlet process priors, which automatically cluster sub-populations and estimate heterogeneous measurement errors. To compare three semiparametric models with the parametric model we propose a penalized posterior Bayes factor. We compare the performance of our semiparametric hierarchical Bayesian approaches with that of the parametric Bayesian hierarchical approach. Simulation results suggest that our semiparametric approaches are more robust and flexible. Our gastric emptying studies from equine medicine are used to demonstrate the advantage of our approaches.     

Simple Transformation Techniques for Improved Non-parametric Regression

We propose and investigate two new methods for achieving less bias in non- parametric regression. We show that the new methods have bias of order h ⁴, where h is a smoothing parameter, in contrast to the basic kernel estimator's order h ². The methods are conceptually very simple. At the first stage, perform an ordinary non-parametric regression on { x_i , Y_i } to obtain m^ ( x_i ) (we use local linear fitting). In the first method, at the second stage, repeat the non-parametric regression but on the transformed dataset { m^ ( x_i , Y_i )}, taking the estimator at x to be this second stage estimator at m^ ( x ). In the second, and more appealing, method, again perform non-parametric regression on { m^ ( x_i , Y_i )}, but this time make the kernel weights depend on the original x scale rather than using the m^ ( x ) scale. We concentrate more of our effort in this paper on the latter because of its advantages over the former. Our emphasis is largely theoretical, but we also show that the latter method has practical potential through some simulated examples.     

Development of r,T hybrid sampling plans for exponential lifetime distributions

SUMMARY In the original hybrid reliability acceptance sampling plan RASP developed by Epstein for the exponential lifetime distribution, the sample size n and the number of failures r to be observed are determined given the truncation time T . However, these plans cannot be used when test items are expensive and or limited in number. Therefore, one wishes to have a plan in which n is given. In this paper, we develop hybrid RASPs in which r and T are determined, given n. These plans are tabulated for various combinations of parameter values, so that one may easily determine an appropriate plan.     

To market, to market: the changing face of grocery retailing

Over the past few years, grocery retailing has undergone a tremendous transformation which was driven mainly by changing consumer characteristics. In order to accommodate these changes, the industry has responded in three ways. The most important of these is the introduction of new technology, particularly efficient consumer response (ECR). The second change has to do with innovations in product and/or service offerings. The final transformation is the organisational restructuring and the increasing number of mergers and acquisitions in the industry at both the manufacturer and retailer levels. The implications of these transformations on the marketing mix, productivity and manufacturer-retailer relationships are discussed.