• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.1013-1025
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• 2016

The purpose of this study was to analyze longitudinal effect of physical education activity (PEA) score on self-rated health evaluation change (SHEC). This study used hierarchical linear and nonlinear models to investigate of the SHEC during the transition into adolescence (from middle school 1st to high school 2nd grade). Using the Korea children and youth panel survey (KCYPA), data were collected over the course of five years (from 2010 and 2014). HLM 6.8 computer program was used to analyze the data. The result were as follows. First, boys' SHEC increased across the five years, and girls' SHEC decreased across the five years. Second, boys' the self-rated health was increased across the three years and decreased across the two years. Third, girls' the self-rated health was increased across the two years and decreased across the three years. Fourth, the PEA score of 1st grade of high school showed a significant positive association with the boys' SHEC. Fifth, the PEA score of 1st grade of middle school showed a significant negative association with the girls' SHEC.

• Korean Public Administration Review
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• v.48 no.4
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• pp.109-132
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• 2014

본 연구는 조직관리자의 조직 내부 및 외부관리 노력과 관리경력 등 관리자의 개인적 특성이 조직구성원의 직무만족에 미치는 영향에 관한 실증적 분석을 실시한다. 층화군집추출로 표집된 한국의 150개 중학교에 대해 3년간 학교, 교장 및 교사 조사를 통해 얻어진 다중원천 자료에 근거하여 위계적 선형모형(HLM)분석을 실시한 결과, 조직관리자인 교장의 관리경력 등 개인적 특성과 함께 교장의 내부관리 노력과 상부기관 및 학부모 등 주요 이해관계자에 대한 의견수렴 등 외부관리 노력이 모두 교사들의 직무만족에 긍정적 영향을 미치고 있음을 발견하였다. 이러한 결과는 선행연구에서 제시하는 개인 및 조직수준 직무만족 설명변수들인 교사의 인구통계학적 특성, 직무동기, 자기효능감, 학교유형, 조직규모, 소재지역, 학교자원 등을 모두 통제한 상태에서 나타났다는 점에서 최근 공공관리 문헌에서 주목받고 있는 관리가 중요하다(management matters)는 주장의 한국적 맥락에서의 타당성을 지지하고 있다.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1009-1020
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• 2010

In this study, we applied a hierarchial linear model to Anyang city data because students and their schools are hierarchial data structure. As a result, main factors which affect parents' satisfaction to school which their children go to are parents' satisfaction to Anyang city's education policies and areas which their schools located at. We suggest based on the analysis by this hierarchial linear model that if Anyang city make educational policies more efficient and effective in order for students to study in public school without private education and if Anyang city improve environment related with school like those of new cities, parents' satisfaction to school which their children go to will be increased.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.65-75
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• 2015

This paper analyzes the determinants of wage for the college and university graduates utilizing both individual-level and industry-level variables. We note that wage determination has multi-level structure in the sense that individual wage is influenced by individual-level variables (level-1) and industry-level (level-2) variables. Then, the assumption that individual wage is independent in the classical regression is violated. Therefore, this paper utilizes the hierarchical linear model (HLM). The major results are the followings. First, the multiple correspondence analysis including level-1 and 2 variables reveals that both level 1 and level 2 variables affects individual wages judging from the fact that the values of level 1 and level 2 variables differ across the different level of individual wage groups. Second, the decision tree analysis including level-1 and 2 variables shows that the most influential variable in wage determination is industry-level wage and the next is industry-level working hour, ages and sex in the decling order in. This suggests that the utilization of the HLM is appropriate since the characteristics of industry is important in determining the individual wage. Third, it is shown that the HLM model is the best compared to the other models which do not take level-1 and level-2 variables simultaneously into account.

• Korean Journal of Child Studies
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• v.27 no.3
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• pp.169-187
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• 2006

A hierarchical linear model(HLM) provides advantages over existing traditional statistical methods (e.g., ordinary least squares regression, repeated measures analysis of variance, etc.) for analyzing multilevel/longitudinal data or diary methods. HLM can gauge a more precise estimation of lower-level effects within higher-level units, as well as describe each individual's growth trajectory across time with improved estimation. This article 1) provides scholars who study children and families with an overview of HLM (i.e., statistical assumptions, advantages/disadvantages, etc.), 2) provides an empirical study to illustrate the application of HLM, and 3) discusses the application of HLM to the study of children and families. In addition, this article provided useful information on available articles and websites to enhance the reader's understanding of HLM.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.935-946
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• 2016

In this paper, we analyzed wage determinants of the vocational high school graduates utilizing both individual-level and work region-level variables. We formulate the models in the way wage determination has multi-level structure in the sense that individual wage is influenced by individual-level variables (level-1) and work region-level (level-2) variables. To incorporate dependency between individual wages into the model, we utilize hierarchical linear model (HLM). The major results are as follows. First, it is shown that the HLM model is better than the OLS regression models which do not take level-1 and level-2 variables simultaneously into account. Second, random effects on sex, maester dummy and engineering dummy variables are statistically significant. Third, the fixed effects on business hours and mean wage of regular job for level-2 variables are statistically significant effect individual-level wages. Finally, parental education level, parental income, number of licenses and high school grade are statistically significant for higher individual-level wages.

• Korean Journal of Childcare and Education
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• v.11 no.2
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• pp.59-85
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• 2015

The purpose of this study was to investigate the effects of child care teachers' emotional supports in individual classrooms on children's social skills, including self-control, assertion, cooperation, and responsibility that were related to their character development. Data were collected in a purposive sample involving 32 teachers working with 646 children at age five and 555 parents of the children. Hierarchical Linear Modeling (HLM) was used to analyze a two-level model. The results showed that there were significant differences among classes with data reported by teachers but characteristics such as teachers' education and work experiences, child-teacher ratio, and type of child care centers as well as teacher's emotional supports did not explain the differences. Children's age and gender, which were predictors at the individual level, significantly explained their level of social skills reported by parents as well as teachers. The findings implied that other predictors influencing differences among classes should be explored in future studies.

• Korean Journal of Social Welfare
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• v.66 no.4
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• pp.77-100
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• 2014

To validate the effects of students' individual factor, school organizational factor, and teacher factor on violent behavior toward peers in school, this study applied Hierarchical Linear Modeling and analyzed it using the HLM 7 program. To this end, it used survey data of students from 50 middle schools in Seoul and Gyeonggi province. A total of 1,777 cases from 50 middle schools were used for individual student-level analysis (Level 1), and used for school-level analysis (Level-2). According to the results of the analysis, student-level variables such as attitude toward violence, experience of child abuse at home, and delinquent peers had significant effects on school violence. The effects of violent discipline by teacher, which are used as a school-level variable, was statistically significant. Based on the result of the study, action plans and policies to resolve school violence were discussed.

• Korean Journal of Child Studies
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• v.30 no.4
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• pp.87-97
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• 2009

This study used Hierarchical Linear Modeling analysis to investigate the effects of individual self-regulated cognitive strategies and public education on middle school students' academic achievement. Participants were 6389 (boys 3287, girls 3102) middle school students from the 2005 data of the Korea Education Longitudinal Study. Results were as follows : (1) there were significant differences among different schools in middle school students' academic achievement, i.e. 20% of variance in English achievement and 15% of variance in mathematics achievement were explained by school differences. (2) Students' elaboration and meta-cognitive strategy influenced academic achievement positively. (3) Predictor variables by ability grouping, supplementary class, and/or self-learning class had no significant effects on students' academic achievement.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1285-1296
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• 2013

The fundamental concerns of this paper are to analyze the effects of student course evaluation using subject characteristic and student characteristic variables. We use a 2-level hierarchical linear model since the data structure of subject characteristic and student characteristic variables is multilevel. Four models we consider are as follows; (1) null model, (2) random coefficient model, (3) mean as outcomes model, (4) intercepts and slopes as outcomes model. The results of the analysis were given as follows. First, the result of null model was that subject characteristics effects on course evaluation had much larger than student characteristics. Second, the result of conditional model specifying subject and student level predictors revealed that class size, grade, tenure, mean GPA of the class, native class for level-1, and sex, department category, admission method, mean GPA of the student for level-2 had statistically significant effects on course evaluation. The explained variance was 13% in subject level, 13% in student level.