• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.278-291
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• 2021

This study performed a longitudinal research on the causal relationship between multidimensionality of problem drinking and poverty, and multidimensional deprivation meaning the inequality, focusing on gender difference. For this, this study examined the latent group of problem drinking change trajectory through the latent class growth analysis targeting total 3,770 men and 5,632 women by using the 6th-year Korea Welfare Panel Study data from 2013 to 2018, and then conducted the multinominal logistic regression analysis to verify the influence of multidimensional deprivation factors on this latent group. The main results of this study are as follows. First, the latent group of problem drinking change trajectory according to gender was classified into three latent groups in both men and women while the development aspect was different from each other. The male latent group with 'moderate level' or higher showed higher level of problem drinking than women. However, in case of 'drinking group with high level' according to gender, as time passed, the men tended to maintain it while the women tended to increase it. Second, in the results of examining the effects of multidimensional deprivation on the latent group of problem drinking change trajectory, the men with more experiences of social deprivation and the women with more experiences of social security deprivation showed the higher possibility to belong to the 'drinking group with high level' compared to the 'drinking group with low level'. Based on such results above, this study discussed the preventive/intervention measures for problem drinking according to gender.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.4
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• pp.202-208
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• 2015

In this study, we propose a new inference algorithm for a multiclass Gaussian process classification model using a variational EM framework and the Laplace approximation (LA) technique. This is performed in two steps, called expectation and maximization. First, in the expectation step (E-step), using Bayes' theorem and the LA technique, we derive the approximate posterior distribution of the latent function, indicating the possibility that each observation belongs to a certain class in the Gaussian process classification model. In the maximization step, we compute the maximum likelihood estimators for hyper-parameters of a covariance matrix necessary to define the prior distribution of the latent function by using the posterior distribution derived in the E-step. These steps iteratively repeat until a convergence condition is satisfied. Moreover, we conducted the experiments by using synthetic data and Iris data in order to verify the performance of the proposed algorithm. Experimental results reveal that the proposed algorithm shows good performance on these datasets.

• Journal of Korean Academy of Nursing
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• v.47 no.6
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• pp.817-827
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• 2017

Purpose: This study aimed to identify latent classes based on major modifiable risk factors for coronary artery disease. Methods: This was a secondary analysis using data from the electronic medical records of 2,022 patients, who were newly diagnosed with coronary artery disease at a university medical center, from January 2010 to December 2015. Data were analyzed using SPSS version 20.0 for descriptive analysis and Mplus version 7.4 for latent class analysis. Results: Four latent classes of risk factors for coronary artery disease were identified in the final model: 'smoking-drinking', 'high-risk for dyslipidemia', 'high-risk for metabolic syndrome', and 'high-risk for diabetes and malnutrition'. The likelihood of these latent classes varied significantly based on socio-demographic characteristics, including age, gender, educational level, and occupation. Conclusion: The results showed significant heterogeneity in the pattern of risk factors for coronary artery disease. These findings provide helpful data to develop intervention strategies for the effective prevention of coronary artery disease. Specific characteristics depending on the subpopulation should be considered during the development of interventions.

• International Journal of Reliability and Applications
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• v.6 no.2
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• pp.101-115
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• 2005

This article provides a new class of multivariate linear failure rate distributions where every component is a mixture of linear failure rate distribution. The new class includes several multivariate and bivariate models including Marslall and Olkin type. The approach in this paper is based on the introducing a linear failure rate distributed latent random variable. The distribution of minimum in a competing risk model is discussed.

• International Journal of Reliability and Applications
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• v.7 no.1
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• pp.55-69
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• 2006

This paper presents a new class of multivariate distributions with Pareto where dependence among the components is characterized by a latent random variable. The new class includes several multivariate and bivariate models of Marshall and Olkin type. It is found the bivariate distribution with Pareto is positively quadrant dependent and its mixture. Some important structural properties of the bivariate distributions with Pareto are discussed. The distribution of minimum in a competing risk Pareto model is derived.

• Korean Journal of Social Welfare Studies
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• v.44 no.3
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• pp.85-112
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• 2013

This study aims to understand the developmental trajectories of life satisfaction among retirees and to examine what factors differentiate different trajectory classes. This study used three waves of longitudinal data from Korean Retirement and Income Study and data collected every two years(2005, 2007, and 2009). Subjects were respondents aged 50-69 who identified to be retired between wave 1 and wave 2. Finally, this study used 243 respondents for final data analysis. Life satisfaction was measured by seven items. The latent class growth model and multiple logistic regression model were used for data analysis. This study identified three distinct trajectory classes: high stable class(47.7%), high at the early stage but decreased class(42.8%), and low at the early stage and then decreased class(9.5%). This study founded that approximately 50% of the retirees experienced the decline of life satisfaction after retirement and about 10% of the sample was the most vulnerable group. This study analyzed what factors make different among the distinct trajectory groups. As a results, retirees who experienced the improvement in health change were more likely to be in 'high stable class' compared to 'hight at the early stage but decreased class'. In addition, retirees who were less educated, maintained the same health status rather than the improvement, worked as a temporary or a day laborer, and had less household income were more likely to belong to 'low at the early stage and then decreased class' relative to 'high stable class'. This study suggests that there are distinct three trajectories on life satisfaction among the retirees and finds out factors differentiating between trajectory groups. Based on these findings, the study discusses the implications for social work practice and further study.

• Survey Research
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• v.10 no.3
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• pp.37-58
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• 2009

The purpose of this study were to identify the subgroups (i.e., latent classes) depending on early adolescents' change patterns in aggression and to test the effects of individual-background variables on determining the latent classes. For these goals, we applied Nagin's(1999) semi-parametric group-based approach to the Korean Youth Panel Study. Results showed that four latent classes were identified, which could be defined based on the patterns as low-level group, increasing group, intermediate-level group, and high-level group. By adding gender, self-control, parent attachment, teacher attachment, and the number of delinquent friends to the unconditional latent class model, we tested the effects of the variables on the latent classes. Multinomial logit analysis showed that gender, self-control, teacher attachment, and the number of delinquent friends were significant determinants of the latent classes. Findings from this study suggest the need to consider heterogeneity in the study of early adolescents' aggression to facilitate more refined targeting of intervention program.

• Journal of the Korean Society of Clothing and Textiles
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• v.35 no.12
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• pp.1440-1453
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• 2011

Proper consumer segmentation is receiving more attention from industry professionals as markets become more diverse and consumer-centered. Researchers have recognized the limitations of the traditional cluster analysis technique and this research study analyzes market segmentation using Mixture-model or latent-class segmentation. This study used a questionnaire to determine the characteristics of clothing shoppers using a new technique that proved its superiority over traditional techniques. Questions included items measuring fashion shopping behavior, store choice criteria, apparel consumption styles, price perception by product type, and demographic characteristics. Data were collected from 1074 males and females in their 20s and 30s through an online survey. SPSS 16.0 and Latent GOLD 4.0 were used to analyze the data. The ideal typology of clothing shoppers using the Mixture-model were: 'brand loyalty orientated group', 'group of conservative late 30s', 'group of pleasure-emotion early 20s', 'value oriented consumer product with high-income group', 'group of eco/symbol oriented consumer', and 'group of utility/goal oriented male consumer'. This study showed differences in fashion product purchasing behavior by conducting market segmentation for clothing shoppers using the Mixture-model.

• Korean Journal of Social Welfare Studies
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• v.48 no.4
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• pp.157-185
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• 2017

This study aimed to explore the trajectories of economic preparations for the aging among people with physical disabilities and to identify the determinants according to the Andersen model. For this study, data were drawn from Panel Survey of Employment for the Disabled (PSED). A total of 1,847 samples were used from the second to the eighth wave. Latent class growth model was conducted to explore the longitudinal change classes for the disabled, and the multinominal logistic regression analysis was conducted to examine the influence of the determinants. As a result, four classes were identified: preparation decrease group, continuous non-preparation group, preparation increase group, and continuous preparation group. Each group was found to be associated deferentially with education level, family income, socioeconomic status, employment, home ownership, national basic livelihood security recipient status, and ADL. These findings proposed the practical and political implications for the strategies concerned with facilitating the economic preparations for the aging among the disabled.

• Korean Journal of Culture and Social Issue
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• v.25 no.4
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• pp.325-351
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• 2019

The present study examined patterns of co-occurrence between DSM-5 posttraumatic stress disorder(PTSD) symptoms and posttraumatic growth(PTG) among Korean populations(n= 860). Latent profile analysis was used to identify subclasses and suggested that the 3-class model fit best: (1) Low PTSD/Mild PTG group (2) Low PTSD/High PTG group; (3) High PTSD/High PTG group. Class membership was predicted by demographic variables, social isolation, and frequency of traumatic experiences. Classes also differed with respect to self-destructive behaviors(binge eating, non-suicidal self-injury, and problem drinking). These findings contribute to future research about the coexisting patterns of PTSD and PTG, and to identify high-risk individuals who suffer from trauma-related problems in clinical practice.