• The Journal of the Korea Contents Association
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• v.14 no.2
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• pp.294-307
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• 2014

The purpose of this study is to examine the trajectory of early adolescent aggression and to assess the effects of perceived family factors on it. This study investigated the changes in aggression over time and the effects of three family factors, parental attachment, parental monitoring, and family conflict, on the changes using multilevel modeling. The data from Korea Youth Panel Survey(KYPS) of fourth graders who were followed over five years were analyzed. The results indicated that there was a significant average increase followed by a slight decrease in aggression over time; that is, the data followed a quadratic trend. Parental attachment, parental monitoring, and family conflict had significant time-independent effects on aggression, while only family conflict had a significant time-dependent effect on aggression. These results imply that family factors need to be emphasized in planning prevention and intervention programs to reduce aggression during adolescence.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.422-433
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• 2021

At this point in time when active participation in renewable energy projects is required, basic information on growth engines and substantial promotion strategies for participation in renewable energy projects is needed. According to the this study tried to provide basic information for vitalizing participation in the renewable energy business by analyzing the factors affecting the new energy business participation roadmap using the multi-layered model. As a result of this study, it can be seen that in order to achieve an effective new energy business participation roadmap, it is necessary to re-establish the new and renewable energy business participation factors by industry. Specifically, it is necessary to prepare appropriate countermeasures such as the leading organization of the project, profit distribution method, green industry financial support, project implementation method, power plant location, and comprehensive long-term strategy, and there is an institutional approach that can promote the development of related industries. found to be necessary. Above all, it suggested that in order to achieve an effective new energy project participation roadmap, an institutional approach is needed that can expand the supply of new and renewable energy while minimizing the burden on the national economy and promote the development of related industries.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.763-776
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• 2020

Onions show severe volatility in production and price because crop conditions highly depend on the weather. The government has designated onions as a sensitive agricultural product, and prepared various measures to stabilize the supply and demand. First of all, preemptive and reliable information on predicting onion production is essential to implement appropriate and effective measures. This study aims to contribute to improving the accuracy of production forecasting by developing a model to estimate the final weight of onions bulb. For the analysis, multi-level model is used to reflect the hierarchical data characteristics consisting of above-ground growth data in individual units and meteorological data in parcel units. The result shows that as the number of leaf, stem diameter, and plant height in early May increase, the bulb weight increases. The amount of precipitation as well as the number of days beyond a certain temperature inhibiting carbon assimilation have negative effects on bulb weight, However, the daily range of temperature and more precipitation near the harvest season are statistically significant as positive effects. Also, it is confirmed that the fitness and explanatory power of the model is improved by considering the interaction terms between level-1 and level-2 variables.

• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.237-254
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• 2020

Housing vacancies have become a major issue in urban areas, there have been many efforts to address this issue at the national and local levels. The purpose of this paper is to investigate the factors contributing to housing vacancies in old town Incheon in South Korea. In particular, the research focuses on examining the effects of multiple levels of factors on housing vacancies in a comprehensive way; the three levels of factors were identified with a literature review including housing (Level 1), Neighborhood (Level 2), and Region (Level 3). A multi-level logistic regression model was used to examine the relationship between 13 factors in three spatial levels and housing vacancies. As a result, the factors in all three levels were able to explain housing vacancies including site area and shape, proximity to major roads (Level 1), ratio of houses in designated urban renewal area and slope (Level 2), and ratio of the elderly living alone, land price, changes in land price and ratio of new houses (Level 3). These results show that the combination of the physical inferiority of the housing site and the neighborhood environment and the economic and social vulnerability of the region is likely to increases the number of vacant houses. This study also suggested that a multi-dimensional policy strategy is needed to solve the problem of housing vacancies, and urban policies, such as supplying new housing or urban renewal area designation, should be carefully implemented in a way not to create housing vacancies.

• 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.

• Journal of the Korea Convergence Society
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• v.12 no.5
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• pp.313-326
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• 2021

This study was to introduce ecological momentary assessment and show how to apply it to real-world research. As preliminary study for sustainable development, the result explained growth model using senior's longitudinal data and suitability of multi-level model in EMA data with regression analysis. The total variance of dependent variable was determined through a base model with only intercept and approximately 47% of total variance was caused by individual differences and 53% by time point differences. Second model was used to verified that each individual has a different effect on the senior vitality and effect on time was not significant. This is because it is the result of a preliminary stage where treatment is not involved and there is no significant change in process of collecting EMA data without external intervention. Third model that add gender as an independent variable showed significant change in both time and gender. Finally compared the PRD for each model and found models that without gender variables fit the data more effectively. This suggests that studies dealing with longitudinal data such as EMA data should adopt multi-level model that can measure individual characteristics, taking into account respondents' time and context.

• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.299-304
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• 2002

본 연구에서는 자궁 내 태아의 발육지연이 주산기 사망률 및 이환율을 증가시키는 고위험 임신의 한 예로써, 태아 발육제한증과 관련한 비선형적인 자료를 통계적인 방법으로 접근하는데 초점을 두었다. 이에 정상태아와 발육제한증 태아를 판별하기 위한 분석을 실시함에 있어 신경망 이론 중 하나인 다층 퍼셉트론 모형으로 예측하고자 하였다.

• The Mathematical Education
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• v.62 no.2
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• pp.195-209
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• 2023

This study examined the effect and structural relationship of math teachers' teaching ability and class activity types on learners' value perception, confidence, and interest of mathematics at the student level and teacher level. To this end, data from 2nd graders of korea middle school in TIMSS 2019 were applied to the multilevel structural equation model. As a result of the analysis, the teaching ability of math teachers had a positive effect on value perception, confidence, and interest of mathematics at the student level and teacher level. Also, math value perception and math confidence had a positive effect on math interest. and it was confirmed that the teaching ability of math teachers indirectly had a positive effect on math interest by mediating math value perception and math confidence. In addition, the math class activity of applying what was learned to problems had a positive effect on math value perception, but it had a negative effect on math interest. and the class activity of the same ability group had a positive effect on math confidence and math interest. This study presents meaningful implications for math classes in the school field through a multilevel analysis of the student level and the teacher level.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1283-1293
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• 2022

The purpose of this study is to predict residual chlorine in order to maintain stable residual chlorine concentration in sedimentation basin by using artificial intelligence algorithms in water treatment process employing pre-chlorination. Available water quantity and quality data are collected and analyzed statistically to apply into mathematical multiple regression and artificial intelligence models including multi-layer perceptron neural network, random forest, long short term memory (LSTM) algorithms. Water temperature, turbidity, pH, conductivity, flow rate, alkalinity and pre-chlorination dosage data are used as the input parameters to develop prediction models. As results, it is presented that the random forest algorithm shows the most moderate prediction result among four cases, which are long short term memory, multi-layer perceptron, multiple regression including random forest. Especially, it is result that the multiple regression model can not represent the residual chlorine with the input parameters which varies independently with seasonal change, numerical scale and dimension difference between quantity and quality. For this reason, random forest model is more appropriate for predict water qualities than other algorithms, which is classified into decision tree type algorithm. Also, it is expected that real time prediction by artificial intelligence models can play role of the stable operation of residual chlorine in water treatment plant including pre-chlorination process.

• Survey Research
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• v.8 no.2
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• pp.21-42
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• 2007

In the present study, we studied the change patterns of adolescents' overt aggression during the middle school 2nd to the high school 1st grades and the effects of ecological factors on the change. For the research goals, we applied multi-level models to the Korean Youth Panel data. Results showed that adolescents' overt aggression decreased significantly during the period. Gender(males recoded as 1) and self-control had negative effects on the initial status(middle school 2nd grade) while the number of delinquency peers had a positive effect. On the other hand, gender and self-control showed positive effects on the change rate. The major strengths of the research are the study of various ecological factors and the longitudinal design. Few studies of adolescents' aggression have incorporated these methodological and substantive characteristics.