Role of Temperament,Parenting Behaviors,and Stress on Turkish Preschoolers’ Internalizing Symptoms

Child‐ and family‐related factors that predict internalizing symptoms are understudied in preschool years and have a negative influence on children's functioning. We examined observational assessments of preschoolers' temperamental fearfulness and exuberance, mother reports of negative control, warmth, and parenting stress in a sample of 109 Turkish preschoolers. High temperamental fearfulness and low joyful/exuberant positive affectivity in addition to low warmth and high parenting stress had significant effects on internalizing symptoms. Parenting stress had both direct and indirect relations to internalizing symptoms via lower maternal warmth. When comorbid elevations in externalizing symptoms were controlled, the results were consistent with the interpretation that poor parenting practices and stress associated with the parenting role predict maladaptation in general but that the specific form of maladaptation may be best predicted by individual differences in children's temperamental characteristics. This study contributes to our understanding of risk and protective factors that predict preschoolers' internalizing symptoms with a sample from a non‐Western population. These findings can guide early prevention and intervention programs to address internalizing problems in a culturally‐sensitive way.     

Variable selection in elliptical linear mixed model

Variable selection in elliptical Linear Mixed Models (LMMs) with a shrinkage penalty function (SPF) is the main scope of this study. SPFs are applied for parameter estimation and variable selection simultaneously. The smoothly clipped absolute deviation penalty (SCAD) is one of the SPFs and it is adapted into the elliptical LMM in this study. The proposed idea is highly applicable to a variety of models which are set up with different distributions such as normal, student-t, Pearson VII, power exponential and so on. Simulation studies and real data example with one of the elliptical distributions show that if the variable selection is also a concern, it is worthwhile to carry on the variable selection and the parameter estimation simultaneously in the elliptical LMM.     

Fostering Undergraduate Data Science

ABSTRACT

Data Science is one of the newest interdisciplinary areas. It is transforming our lives unexpectedly fast. This transformation is also happening in our learning styles and practicing habits. We advocate an approach to data science training that uses several types of computational tools, including R, bash, awk, regular expressions, SQL, and XPath, often used in tandem. We discuss ways for undergraduate mentees to learn about data science topics, at an early point in their training. We give some intuition for researchers, professors, and practitioners about how to effectively embed real-life examples into data science learning environments. As a result, we have a unified program built on a foundation of team-oriented, data-driven projects.     

Reactions to cyberbullying among high school and university students

In this study, behavioral and emotional reactions to cyberbullying were investigated by surveying 567 undergraduate-level university students and 211 high school students. Among the study participants, 170 of the undergraduates (29.98%) and 120 of the high school students (56.87%) reported that they had recently been cyberbullied. A four-factor scale with 37 items was used to investigate the behavioral cyberbullying reactions of victimized students. The four factors were revenge, countermeasure, negotiation and avoidance. An additional two-factor scale with 11 items was used to classify victimized students’ emotional reactions as either internalizing or externalizing. Explained variance values of both scales were above 50%, and the factors were found to have acceptable internal consistency coefficients. Behavioral and emotional reactions varied according to gender and school level. Computer self-efficacy and internet use were associated with different reaction types.     

How to Create a Friendly Environment for Innovation? A Case for Europe

Social Indicators Research - It is a misjudgement to assume that R&D subsidies, patent protections or alike are sufficient to promote innovation. In fact, innovations incubate and hatch...     

Understanding the Determinants of Service Channel Preference in the Early Stages of Adoption: A Social Cognitive Perspective on Online Brokerage Services*

In today's increasingly technology‐mediated world, individuals are often confronted with a decision of whether to obtain services through online, self‐service technologies or traditional, nontechnological alternatives. Understanding the mechanisms by which consumers choose among these competing service channels represents an important concern for organizations, consumers, and Web site designers. This study develops a research model based on Social Cognitive Theory to explain and predict service channel preferences that arise in the early stages of adoption, before a consumer conducts business using a particular channel. The model is subsequently tested in the brokerage services context, using observations obtained via survey. Given the growing popularity of online investing combined with the challenging prospect of making optimal decisions in an inherently risky environment, the context offers insights of practical and theoretical importance. The results suggest that task‐specific self‐efficacy beliefs serve as the activating mechanism kicking off a chain of psychological events that entice consumers to favor a particular service channel. Higher levels of self‐efficacy induce individuals to prefer the online approach. In addition to its direct effect on preference for the online service channel, higher levels of self‐efficacy influence one's propensity to take risks and expectations of performance‐oriented rewards, which, in turn, sway consumers to favor the online service channel. Furthermore, self‐efficacy and perceptions concerning the credibility of online information interact to affect service channel preference. Consumers are more likely to prefer the online service channel when they view themselves as capable and perceive online sources to be credible. Implications for theory and practice are discussed in light of the findings.     

The health insurance market,labor unions,and utilization of cancer screening

The present study examines the effect of labor market characteristics, especially labor unions, on the use of two representative cancer screening services, namely the mammogram and the Pap smear, given the level of competition in the health insurance market. The role of labor unions is illustrated by means of estimated probabilities based on regression results that consider, for the first time, both health insurance and labor market variables in the same model by employing a multilevel analysis, a technique not previously used in prevention studies. The results suggest that competition among health insurance plans may actually reduce the use of preventive care whereas union membership may mitigate such negative impacts.     

Combining decision tree and MAUT for selecting a country for a global manufacturing facility

The paper presents a multi-phase approach for selecting a country in which to locate a global manufacturing facility. An influence diagram is used to frame the decision. A decision tree then analyzes uncertainties regarding cost and generates a risk profile. The risk profile becomes one of the measures in an MAUT model that incorporate a wide range of factors. This sequential approach of using the output from a decision tree as input to MAUT is demonstrated with an example involving an auto supplier locating a new plant in one of five countries. Three decision makers were interviewed to determine the weights and the shape of the individual utility curves. The paper identifies, clearly defines, and incorporates a variety of measures for which national data are readily available. This list is broader and less subjective when compared to other examples reported in the literature.     

Comparison of estimation methods for the finite population mean in simple random sampling: symmetric super-populations

In this paper, a new estimator combined estimator (CE) is proposed for estimating the finite population mean ¯ Y _N in simple random sampling assuming a long-tailed symmetric super-population model. The efficiency and robustness properties of the CE is compared with the widely used and well-known estimators of the finite population mean ¯ Y _N by Monte Carlo simulation. The parameter estimators considered in this study are the classical least squares estimator, trimmed mean, winsorized mean, trimmed L-mean, modified maximum-likelihood estimator, Huber estimator (W24) and the non-parametric Hodges–Lehmann estimator. The mean square error criteria are used to compare the performance of the estimators. We show that the CE is overall more efficient than the other estimators. The CE is also shown to be more robust for estimating the finite population mean ¯ Y _N , since it is insensitive to outliers and to misspecification of the distribution. We give a real life example.