• Journal of the Korean Data and Information Science Society
• /
• v.25 no.6
• /
• pp.1439-1447
• /
• 2014

Most of literatures on Korean child aggression are based on using the cross-sectional data sets. Although there is a related study with a longitudinal data set, it is assumed that the data sets measured repeatedly in the longitudinal data are mutually independent. A longitudinal data analysis for Korean child aggression is then necessary. This study is to analyze the effect of child development outcomes including academic achievement, self-esteem, depression anxiety, delinquency, victimization by peers, abuse by parents and internet using time on child aggression with Korea Welfare Panel Study data observed three times between 2006 and 2012. Since Korea Welfare Panel Study data have missing values, the missing at random is assumed. The linear mixed effect model and the restricted maximum likelihood estimation are considered.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.20 no.9
• /
• pp.2770-2781
• /
• 1996

Longitudinal shear modulus of continuous fiber reinforced 2-phase composites is predicted by theoretical and numerical analysis methods. In this paper, circular, hexagonal and rectangular shapes of reinforced fiber are considered using unit cell concept. And fiber array is regular rectangular and hexagonal fiber arrangement. Longitudinal shear modulus is a function of fiber distribution pattern and fiber volume change. It is found that the rectangular array has a higher longitudinal shear modulus than the hexagonal one. Also, the rectangular fiber shape in lower fiber volume fraction and the circular fiber shape in higher fiber volume fraction show the higher longitudinal shear modulus. And it has been found that the theoretical and numerical predictions of the longitudinal shear modulus give a good agreement with the experimental data at lower fiber volume fraction. Both the distance and stress transfer between the fibers are discussed as the major determing factors.

• Journal of Fashion Business
• /
• v.6 no.6
• /
• pp.78-88
• /
• 2002

The purpose of this study is to provide for some basic data useful to production of the apparels fit and measured well for the Chinese men. For this purpose, 389 men aged between 20 and 49 and living in Beijing and Shanghai, China were sampled to be measured for their constitutions. Then, their constitutions were classified and thereupon, according to the Men's Wear Specifications (GB/T 1335.1-1997), National Standards of People's Republic of China. The collected data were statistically processed using SAS 6.12 for technical statistical analysis, correlation analysis, factor analysis, group-wise analysis. The results of this study can be summarized as follows; 1. As a result of the factor analysis aiming to determine Chinese men's constitutional components, five components could be identified: constitutional obesity, lateral body size, longitudinal body size, shoulder and back width, and shoulder drooping. 2. As a result of classifying Chinese men's constitutions according to drop measurements, four types could be identified. Y type had the lowest obesity and the highest longitudinal body size. A type had a lower obesity and had an average longitudinal body size. B Type had the second highest obesity, the smallest longitudinal body size and shoulders/back width. C Type had the highest obesity, upper body length and shoulders/back width. 3. In terms of distribution, 'B' type (39.10%) of the sample, followed by 'A' type (29.26%), 'C' type (19.95%) and 'Y' type (11.70%). In all, the results of this study suggests that 'B' type represents the Chinese men in contrast with GB specifying that 'A' type represents the Chinese men. On the other hand, Beijing region was dominated most by 'B' type (37.06%), followed by 'A' type (28.82%), 'C' type (22.35%) and 'Y' type (11.76%), while Shanghai region was dominated most by 'B' type (41.13%), followed by 'A' type (31.21%), 'C' type (19.15%) and 'Y' type (8.51%).

• Journal of the Korea Convergence Society
• /
• v.10 no.2
• /
• pp.217-225
• /
• 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 Korean Statistical Society
• /
• v.29 no.2
• /
• pp.201-217
• /
• 2000

The method of generalized estimating equations (GEE) has become very popular for the analysis of longitudinal data. We extend this work to the use of M-estimators; the resultant regression estimates are robust to heavy tailed errors and to outliers. The proposed method does not require correct specification of the dependence structure between observation, and allows for heterogeneity of the error. However, an estimate of the dependence structure may be incorporated, and if it is correct this guarantees a higher efficiency for the regression estimators. A goodness-of-fit test for checking the adequacy of the assumed M-estimation regression model is also provided. Simulation studies are conducted to show the finite-sample performance of the new methods. The proposed methods are applied to a real-life data set.

• The Journal of Korean Association of Computer Education
• /
• v.23 no.1
• /
• pp.53-61
• /
• 2020

In the information society, the ability of learners to use computers to conduct self-directed learning is important. Indeed, the higher the computer's ability to use computers, the more the academic achievement needs to be analyzed. The purpose of this study was to identify longitudinal trajectories of student awareness of ICT literacy and frequency of computer use. We also examined the effects of the longitudinal patterns on academic achievement and college major choice. A non-parametric approach, K-means for longitudinal data(KML) algorithm, was conducted using 9-year longitudinal data from Seoul Education Longitudinal Study (2010-2018). Findings indicated that a pattern presenting a higher awareness of ICT literacy and frequency of computer use showed better academic achievements and was likely to prefer to choose engineering-related majors.

• International Journal of Control, Automation, and Systems
• /
• v.5 no.4
• /
• pp.410-418
• /
• 2007

For the purpose of fault detection of the primary control surface, real-time estimation of the longitudinal stability and control derivatives of the DURUMI-II using the flight data is considered in this paper. The DURUM-II, a research UAV developed by KARI, is designed to have split control surfaces for the redundancy and to guarantee safety during the fault mode flight test. For fault mode analysis, the right elevator was deliberately fixed to the specified deflection condition. This study also mentions how to implement the multi-step control input efficiently, and how to switch between the normal mode and the fault mode during the flight test. As a realtime parameter estimation technique, Fourier transform regression method was used and the estimated data was compared with the results of the analytical method and the other available method. The aerodynamic derivatives estimated from the normal mode flight data and the fault mode data are compared and the possibility to detect the elevator fault by monitoring the control derivative estimated in real time by the computer onboard was discussed.

• Journal of the Korean Data and Information Science Society
• /
• v.24 no.4
• /
• pp.877-883
• /
• 2013

The quadratic inference functions (QIF) method proposed by Qu et al. (2000) and the generalized method of moments (GMM) for marginal regression analysis of longitudinal data with time-dependent covariates proposed by Lai and Small (2007) both are the methods based on generalized method of moment (GMM) introduced by Hansen (1982) and both use generalized estimating equations (GEE). Lai and Small (2007) divided time-dependent covariates into three types such as: Type I, Type II and Type III. In this paper, we compared these methods in the case of Type II and Type III in which full covariates conditional mean assumption (FCCM) is violated and interested in whether they can improve the results of GEE with independence working correlation. We show that in the marginal regression model with Type II time-dependent covariates, GMM Type II of Lai and Small (2007) provides more ecient result than QIF and for the Type III time-dependent covariates, QIF with independence working correlation and GMM Type III methods provide the same results. Our simulation study showed the same results.

• Korean Journal of Childcare and Education
• /
• v.15 no.5
• /
• pp.23-45
• /
• 2019

Objective: The purpose of this study is to identify the longitudinal reciprocal relationship between young children's vocabulary ability and physical aggression in young children. Methods: Two waves of panel data(2013/2015) from the Panel Study of Korean Children were analyzed in this study by using an adapted version of Autoregressive cross-lagged modeling. A total of 306 five-year-old and seven-year-old preschoolers, and their mothers participated in the study. Autoregressive cross-lagged modeling for multiple groups was conducted by using AMOS 24.0. Results: First, vocabulary ability and physical aggression showed stability over time. Second, young children's vocabulary ability(t) had a statistically significant effect on physical aggression(t+1). Conclusion/Implications: This study confirmed the interrelationships of young children's vocabulary ability and physical aggression by examining longitudinal data using the longitudinal analysis method. This study highlights the importance of developing interventions to support language development with aggressive children. The results of the present study can be used as a source in developing policies for aggressive children and their parents.

• Research in Community and Public Health Nursing
• /
• v.31 no.1
• /
• pp.86-95
• /
• 2020

Purpose: The aim of this study was to examine the correlation between school-life adjustment and suicidal ideation in adolescents by applying the latent growth curve models to the longitudinal data. Methods: This study analyzed three waves of data from the Korean Children & Youth Panel Survey (2014~2016). A total of 1,534 students were included in the analysis. In the application of the latent growth curve models to the longitudinal survey data, we analyzed the initial status and growth changes for each wave, identified individual differences in the general characteristics, and examined the direct relationship between the two latent constructs. Results: The analysis revealed that variations in the initial status and rate of school-life adjustment were significant with respect to parents' education level, household income and academic satisfaction. Variations in the initial status and growth rate of suicidal ideation were significantly associated with household income and family structure. The relationship between school-life adjustment and suicidal ideation showed a negative correlation in which the starting value of the former increased and that of the latter decreased and vice versa. Conclusion: The results confirmed that school-life adjustment and suicidal ideation varied according to students' general characteristics. In addition, school-life adjustment was negatively correlated with suicidal ideation, thereby highlighting students' ability to adjust as an important factor influencing their suicidal thinking.