• Journal of the Korea Convergence Society
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• v.10 no.2
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• pp.217-225
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• 2019

The Latent Growth Modeling(LGM) is known as the typical analysis method of longitudinal data and it could be classified into unconditional model and conditional model. It is common to assume that the growth trajectory of unconditional model of LGM is linear. In the case of quasi-linear, the methodology for improving the model fitness using Sequential Pattern of Association Rule Mining is suggested. To do this, we divide longitudinal data into quintiles and extract periodic changes of the longitudinal data in each quintiles and make sequential pattern based on this periodic changes. To evaluate the effectiveness, the LGM module in SPSS AMOS was used and the dataset of the Youth Panel from 2001 to 2006 of Korea Employment Information Service. Our methodology was able to increase the fitness of the model compared to the simple linear growth trajectory.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.61-68
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• 2015

In recent times, the median filtering (MF) detector as a forensic tool for the recovery of forgery images' processing history has concerned broad interest. For the classification of MF image, MF detector should be designed with smaller feature set and higher detection ratio. This paper presents a novel method for the detection of MF in altered images. It is transformed from BMP to several kinds of MF image by the median window size. The difference distribution values are computed according to the window sizes and then the values construct the feature set same as the MF window size. For the MF detector, the feature set transformed to the model specification which is computed using latent growth modeling (LGM). Through experiments, the test image is classified by the discriminant into two classes: the true positive (TP) and the false negative (FN). It confirms that the proposed algorithm is to be outstanding performance when the minimum distance average is 0.119 in the confusion of TP and FN for the effectivity of classification.

• (The)Korea Educational Review
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• v.23 no.1
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• pp.205-230
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• 2017

Drawing on third to fifth wave data from the Longitudinal Study of North Korean Migrant Youths' Education, we examined the longitudinal relationship between social capital of North Korean Migrant Youths and school adjustment using latent growth modeling(LGM). Specifically, we sought to answer the following research questions: Do social capital and school adjustment among North Korean Migrant Youths change over time? Is there a relationship between the changes in social capital and school adjustment among these students? Our LGM results showed that trends in social capital and school adjustment among these students were not fixed but changed over time. While the social capital developed by these students was found to influence school adjustment at the time of its development, it did not continue to influence changes in school adjustment over time. Changes in school adjustment of North Korean migrant youths were affected by changes in social capital. These results suggest that there is room for gradual improvement of school adjustment level by strengthening social capital of North Korean migrant youths.

• Journal of Digital Convergence
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• v.16 no.6
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• pp.85-93
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• 2018

The Latent Growth Modeling(LGM) is known as the arising analysis method of longitudinal data and it could be classified into unconditional model and conditional model. Unconditional model requires estimated value of intercept and slope to complete a model of fitness. However, the existing LGM is in absence of a structured methodology to estimate slope when longitudinal data is neither simple linear function nor the pre-defined function. This study used Sequential Pattern of Association Rule Mining to calculate slope of unconditional model. The applied dataset is 'the Youth Panel 2001-2006' from Korea Employment Information Service. The proposed methodology was able to identify increasing fitness of the model comparing to the existing simple linear function and visualizing process of slope estimation.

• Korean Journal of Child Studies
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• v.28 no.5
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• pp.127-141
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• 2007

The purpose of this research was to analyze the trajectory of child's academic attainment and the effect of family socioeconomic background on the trajectory. Data were part of the Korea Youth Panel Survey 2003-2005(Middle School 2) and were analyzed by Latent Growth Curve Modeling(LGM). The degree of child's academic attainment decreased over 3 years. Socioeconomic status variables that influenced academic trajectory were family poverty, parent's attainments in scholarship, and family structure. Findings from this study suggest that societal support for low socioeconomic status families is needed for improvement of academic attainment of their children.

• Journal of Technology Innovation
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• v.28 no.1
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• pp.1-30
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• 2020

The government has implemented policies to increase university technology commercialization while supporting university research over time. This paper adopts the neo-institutional theory and examines the effect of change in the government research funds that universities have received overtime on the change in their technology commercialization performance. It also investigates a location (Seoul metro or others) effect on the relationships. Using latent growth curve modeling (LGM), which is widely used for time-varying analysis, this study longitudinally analyzes 138 universities in South Korea over the past nine years from 2009 to 2017. The results indicate that the growth in the annual government research funds that universities attain affects the growth in the economic value of technology transfers. In addition, the relationship is stronger for universities in Seoul metropolitan areas than those in other areas. The relationships are intact with one-year lagging effects. The findings help understand the effectiveness of government R&D policies for promoting technology commercialization.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.31-41
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• 2020

This study analyzed parents' school satisfaction longitudinally using data from the 1st, 3rd, and 5th wave data of the Korea Education Longitudinal Study(KELS)2013. The subjects of analysis are parents who responded without dropping out in the first, third and fifth panel of the KELS2013, and 4,227 cases that had no missing values in the variables were selected for the sample to input for analysis of the latent growth modeling(LGM). As a result, it is confirmed that the parents' education, educational support, and children's academic achievement have a positive effect on the parents' school satisfaction. But the parents' educational view and education cost have a negative effect on that. The results of this study are expected to be important information to help enhance the primary function of the school.

• Journal of Families and Better Life
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• v.35 no.1
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• pp.125-137
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• 2017

The purpose of this study was to investigate the longitudinal relationship between Korean youth's social withdrawal, depression and community sense mediated by achievement values. For this purpose, we analyzed three years of the longitudinal panel data (2011-2013) of the Korean Children and Youth Panel Survey (KCYPS). Data were collected from 2,351 first year middle school students using the latent growth model using SPSS 18.0 and AMOS 22.0. The main analysis results were as follows. First, social withdrawal and depression decreased and community sense increased as time passed. These results supported the linear change model. Second, the initial status of social withdrawal and depression had effects on the initial status and change rates of community sense. Achievement values, the partial mediator, had a positive influence on initial community sense but had a negative influence on change rates of community sense. We discussed how to improve Korean youth's community sense based on these results.

• Journal of the Korean Home Economics Association
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• v.48 no.5
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• pp.25-48
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• 2010

The purpose of this study was to employ the Latent Growth Curve Model(LGM) to investigate the developmental trajectories of children's internalizing and externalizing problem behaviors and to identify predictors that might have an effect on change and the level of developmental trajectories. Furthermore, we classified the developmental trajectories of children's internalizing and externalizing problem behaviors, and also analyzed factors which caused differences in developmental trajectories by Semi-Parametric Group-based Modeling. This study used data from wave 1-4(2004~2008) of elementary school fourth grade panel of the Korea Youth Panel Survey(KYPS). The results showed that children's internalizing and externalizing problem behaviors changed significantly from the fourth grade of elementary school to the first grade of middle school. The predictors for developmental trajectories of children's internalizing problem behaviors were gender, self-control, parental conflict, deviant peers, and attachment to teachers. The predictors for the developmental trajectories of children's externalizing problem behaviors were gender, self-esteem, self-control, and deviant peers. The developmental trajectories of children's internalizing problem behaviors was classified into three groups. The developmental trajectories of children's externalizing problem behaviors was classified into four groups.

• Journal of Family Relations
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• v.21 no.2
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• pp.77-96
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• 2016

Objectives: The aims of this study are to examine the associations between marital satisfaction and life satisfaction among Korean retirees in later life and to test whether the degrees of associations increased over time. Method: Nationally representative Korean Longitudinal Study of Ageing data from wave 1 (in 2006) to wave 4 (in 2012) was utilized and retirees in later life (65-89 years old, N=402) were analyzed. Latent growth modeling (LGM) and model constraint were applied using Mplus 7.3. Age, sex, household income, subjective health, depressive symptoms and elapsed time after retirement were included as control variables. Results: Linear unconditional LGM fitted the data well and showed gradual decrease in life satisfaction. Conditional LGM revealed significant associations between marital satisfaction and life satisfaction from time 1 to time 4. According to model constraint test, the size of associations between marital satisfaction and life satisfaction did not change with time. Conclusions: To sum up these results, the associations between marital satisfaction and life satisfaction were significant and relatively stable over time among retirees in later life. This study suggests one's spouse is a fundamental component of social convoy among Korean retirees in later life. Therefore, intervention programs targeted toward enhancing marital relationships among retirees' couples will help them to live a better life.