• Journal of Digital Convergence
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• v.10 no.11
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• pp.209-223
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• 2012

The purpose of this study is to examine the moderating effects of emotional intelligence in the relationship between transformational leadership and organizational commitment. To achieve the this research purpose, theoretical and empirical studies related to transformational leadership, organizational commitment, and emotional intelligence were carried out simultaneously. The established hypotheses related to transformational leadership, organizational commitment, and emotional intelligence were verified by the hierarchical regression analysis using SPSS. The result of this research are as followers : First, the hierarchical regression analysis revealed that moderation term was significant(${\beta}$=0.146, p<.01). The interaction term for charisma and emotional intelligence had a significant and positive relationship with organizational commitment. Second, the hierarchical regression analysis revealed that moderation term was insignificant(${\beta}$=2.295, p<.05) The interaction term for inspirational motivation and emotional intelligence had a significant and positive relationship with organizational commitment. Third, the hierarchical regression analysis revealed that moderation term was significant(${\beta}$=0.200, p<.001). The interaction term for intellectual stimulation and emotional intelligence had a significant and positive relationship with organizational commitment. Fourth, the hierarchical regression analysis revealed that moderation term was significant(${\beta}$=2.213, p<.01).

• Communications for Statistical Applications and Methods
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• v.22 no.4
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• pp.349-359
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• 2015

We study a semiparametric Bayesian approach to small area estimation under a nested error linear regression model with area level covariate subject to measurement error. Consideration is given to radial basis functions for the regression spline and knots on a grid of equally spaced sample quantiles of covariate with measurement errors in the nested error linear regression model setup. We conduct a hierarchical Bayesian structural measurement error model for small areas and prove the propriety of the joint posterior based on a given hierarchical Bayesian framework since some priors are defined non-informative improper priors that uses Markov Chain Monte Carlo methods to fit it. Our methodology is illustrated using numerical examples to compare possible models based on model adequacy criteria; in addition, analysis is conducted based on real data.

• Journal of Fisheries and Marine Sciences Education
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• v.27 no.3
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• pp.644-655
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• 2015

This study was planned to examine the moderating effects of depression and anxiety and the relationship between online game addiction and adolescents' delinquency. Data were collected from children and youth's mental health advocacy research by National Youth Policy Institute. The subjects were 409 adolescents aged between 14 and 18. Correlational analysis and hierarchical regression analysis were conducted to test research hypotheses. Results of this study were as follows: first, online game addiction had a significant positive relations with adolescents' delinquency. Second, depression and anxiety were significant positive relations with each other. And depression and anxiety were significant positive relations with adolescents' delinquency. The result from hierarchical regression analysis showed that significant moderating effect of depression was found. But the result wasn't exhibited twithin hat the two-way interaction effects of depression. On the other hand, result from hierarchical regression analysis showed that significant moderating effect of anxiety wasn't found. In conclusion, this study proposed the need for counseling approach focused on 'depression' in order to reduce the adolescent's delinquency.

• International Journal of Contents
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• v.13 no.3
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• pp.65-74
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• 2017

Women's menopause is a natural process that every woman must eventually experience, but changes in hormones before and after menopause can serve to produce life-threatening crises in some situations, with individual differences. Data for the study was elicited from 22,610 Korean women ranging in age from 45 to 55 years in the 2013 Korean Community Health Survey. Statistical analyses was performed using descriptive, t-test, ANOVA, and hierarchical regression analysis using SPSS IBM 20.0 version. Individual characteristics, lifestyle, history of chronic disease(s), psychological and environmental factors were included as independent and EQ5D weights of Koreans were used as dependent variables. The survey subjects consisted of a total 15,505(58.3%) in their 50s, 1,765 (66.5%) in middle and high school dropouts or graduates, 22,174 (83.3%) living in spouses and 10,534(39.6%) in wages. There was a significant difference in HRQOL among all independent variables except drinking and residential areas. Hierarchical regression analysis showed that age, smoking, obesity and other incidental disease factors (fall, angina, asthma, arthritis, osteoporosis, stroke) had a negative effect on HRQOL. The selected independent variables accounted for 22.7% of HRQOL. It is necessary to find a way to improve HRQOL of Korean perimenopausal women, focusing on the significant variables revealed by the study results.

• Korean Business Review
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• v.22 no.2
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• pp.111-137
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• 2009

The purpose of this study is to examine the moderating effect of emotional intelligence in the relationship between transformational leadership and organizational citizenship behavior. To achieve this research purpose, theoretical and empirical studies related to transformational leadership, organizational citizenship behavior, and emotional intelligence were carried out simultaneously. A field survey was undertaken through questionnaire sampling a population of public organization in Chungchungnamdo. The established hypotheses related to transformational leadership, organizational citizenship behavior, and emotional intelligence were verified by the hierarchical regression analysis using SPSS. The result of this research are as followers : First, hypothesis1 proposed that emotional intelligence will be moderate the effect of charisma on organizational citizenship behavior. The hierarchical regression analysis revealed that moderation term was insignificant. The interaction term for charisma and emotional intelligence had a insignificant and positive relationship with organizational citizenship behavior. Therefore, hypothesis1 was not supported by the data. Second. hypothesis2 stated that emotional intelligence will be moderate the effects of inspirational motivation on organizational citizenship behavior. Hypothesis2 The result of the hierarchical regression analysis show a insignificant interaction between inspirational motivation and emotional intelligence on organizational citizenship behavior. Therefore, hypothesis2 was not supported by the data. Third, hypothesis3 stated that emotional intelligence will moderate the effect of intellectual stimulation on organizational citizenship behavior. The result of the hierarchical regression analysis show a significant interaction between intellectual stimulation and emotional intelligence on organizational citizenship behavior. Therefore, hypothesis3 was supported by the data. Fourth, hypothesis4 proposed that emotional intelligence will moderate effect of individualized consideration on organizational citizenship behavior. The hierarchical regression analysis revealed that the interaction term for individualized consideration and emotional intelligence had a significant and positive relationship with organizational citizenship behavior. Therefore, hypothesis4 was supported by the data. This study revealed that emotional intelligence moderate the relationship between intellectual stimulation, individualized consideration, and organizational citizenship behavior. It concludes that organizational citizenship behavior varies with coalignment of transformational leadership and emotional intelligence.

• Educational Technology International
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• v.22 no.2
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• pp.255-283
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• 2021

In the early 2020, COVID-19 changed the traditional way of teaching and learning. This paper aimed to explore the impact of college students' perception of course quality on their online learning satisfaction. A total of 4,812 valid samples were extracted, and the difference analysis and hierarchical regression analysis were used to make an empirical analysis of college students' online learning satisfaction. The research results were as follows. Firstly, there was no difference in online learning satisfaction among students by gender and grade. Secondly, learning assessment, course materials, course activities and learner interaction, and course production had a significant positive impact on online learning satisfaction. Course overview and course objectives had an insignificant correlation with online learning satisfaction. Thirdly, the total effect of online learning satisfaction was as follows. Course production had the greatest effect, followed by course activities and student-student interactions, followed by course materials. It was the learning evaluation that showed the least effect. This study can provide empirical reference for college teachers on how to continuously improve online teaching and increase students' satisfaction with online learning.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.695-704
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• 2020

Recently, There has been an increasing of utilization IT, and studies have been conducted on predicting learning results. In this study, Learning activity data were collected that could affect learning outcomes by using learning analysis. The survey was conducted at a university in South Chung-Cheong Province from October to December 2018, with 1,062 students taking part in the survey. First, A Hierarchical regression analysis was conducted by organizing a model of individual, academic, and behavioral factors for learning results to ensure the validity of predictors in machine learning. The model of hierarchical regression was significant, and the explanatory power (R²) was shown to increase step by step, so the variables injected were appropriate. In addition, The linear regression analysis method of machine learning was used to determine how predictable learning outcomes are, and its error rate was collected at about 8.4%.

• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.6
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• pp.928-939
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• 2000

This thesis will study the determinants of consumer satisfaction based on the disconfirmation theory. The proposed questions are first, to find out if desire and expectation are conceptually distinct. Second, to study the effects of desire, expectation, perceived performance, desire congruency, and expectation congruency on clothing satisfaction. The data used in this thesis were obtained from a two stage longitudinal survey. SPSS WIN 8.0 was used for the analysis and the following method such as mean, correlation, t-test, hierarchical regression were applied. The results indicate that first, according to the correlation analysis and crosstab analysis, satisfaction and desire were perceived as two different concepts. Second, using the hierarchical regression analysis to compare the effects of determinants of consumer satisfaction, the model of desire, expectation, performance, desires congruency, expectations congruency best explain the clothing satisfaction. Among them, effects of performance had the strongest impact. Expectation did not influence satisfaction but desire did.

• Genomics & Informatics
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• v.16 no.4
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• pp.38.1-38.3
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• 2018

Gene-gene interaction (GGI) analysis is known to play an important role in explaining missing heritability. Many previous studies have already proposed software to analyze GGI, but most methods focus on a binary phenotype in a case-control design. In this study, we developed "Hierarchical structural CoMponent analysis of Gene-Gene Interactions" (HisCoM-GGI) software for GGI analysis with a continuous phenotype. The HisCoM-GGI method considers hierarchical structural relationships between genes and single nucleotide polymorphisms (SNPs), enabling both gene-level and SNP-level interaction analysis in a single model. Furthermore, this software accepts various types of genomic data and supports data management and multithreading to improve the efficiency of genome-wide association study data analysis. We expect that HisCoM-GGI software will provide advanced accessibility to researchers in genetic interaction studies and a more effective way to understand biological mechanisms of complex diseases.

• Journal of Families and Better Life
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• v.21 no.2
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• pp.87-101
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• 2003

The purposes of this study were to analyze causes of wife abuse through married couples as the research subject. The study employed ecological perspective to the study of wife abuse as an multiple dimensional and integrated paradigm combined with isolated theories of other research. The subjects were 369 married couples who live in Gwangju area. Data were analyzed with Cronbach'α, factor analysis, basic statistics, paired-t test, 1-test, ANOVA, Duncan's test, correlation analysis, stepwise multiple regression analysis. and hierarchical regression analysis using the SPSS 10.0 for windows. The major findings were as follows; 1. The psychological abuse score, physical abuse score, and sexual abuse score were lower than median without exception. Hut prevalence rates of wife abuse were considerably serious; 91.9% psychological abuse, 44.4% physical abuse, and 53.7% sexual abuse. 2. The results of the hierarchical regression analysis indicated that the marital conflict had the strongest impact on wife abuse. And the attitude toward wife abuse of husband, hostility of husband, exposure experience of domestic violence during a growth period of husband, perception toward social violence of husband, exposure experience of domestic violence during a growth period of wife, drinking problem of husband, and interpersonal relationships stress of husband had influenced on wife abuse. These variables accounted for 49.5% of variance of wife abuse behaviors. As the result of the study, it concludes that the ecological systemic approach on the cause of wife abuse is useful as a theoretical instrument. Suggestions and implications are made for further research and practical application.