• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.721-732
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• 2018

Latent class analysis (LCA) is an important tool to explore unseen latent groups in multivariate categorical data. In practice, it is important to select a suitable set of variables because the inclusion of too many variables in the model makes the model complicated and reduces the accuracy of the parameter estimates. Dean and Raftery (Annals of the Institute of Statistical Mathematics, 62, 11-35, 2010) proposed a headlong search algorithm based on Bayesian information criteria values to choose meaningful variables for LCA. In this paper, we propose a new variable selection procedure for LCA by utilizing posterior probabilities obtained from each fitted model. We propose a new statistic to measure the adequacy of LCA and develop a variable selection procedure. The effectiveness of the proposed method is also presented through some numerical studies.

• Communications of Mathematical Education
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• v.34 no.1
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• pp.17-39
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• 2020

The purpose of this study is to analyze the mathematical beliefs of students and teachers by Latent Class Analysis(LCA). This study surveyed 60 teachers about beliefs of 'nature of mathematics', 'mathematic teaching', 'mathematical ability' and also asked 1850 students about beliefs of 'school mathematics', 'mathematic problem solving', 'mathematic learning' and 'mathematical self-concept'. Also, this study classified each student and teacher into a class that are in a similar response, analyzed the belief systems and built a profile of the classes. As a result, teachers were classified into three types of belief classes about 'nature of mathematics' and two types of belief classes about 'teaching mathematics' and 'mathematical ability' respectively. Also, students were classfied into three types of belief classes about 'self concept' and two types of classes about 'School Mathematics', 'Mathematics Problem Solving' and 'Mathematics Learning' respectively. This study classified the mathematics belief systems in which students were categorized into 9 categories and teachers into 7 categories by LCA. The belief categories analyzed through these inductive observations were found to have statistical validity. The latent class analysis(LCA) used in this study is a new way of inductively categorizing the mathematical beliefs of teachers and students. The belief analysis method(LCA) used in this study may be the basis for statistically analyzing the relationship between teachers' and students' beliefs.

• Journal of The Korean Association For Science Education
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• v.37 no.1
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• pp.113-123
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• 2017

The purpose of this study is to investigate engineering students' attitude toward convergence and relevance with engineering education accreditation, gender, and academic year and attitude toward convergence. To be specific, fist, we examined whether the instrument for measuring attitudes toward convergence were reliable and valid for engineering students. Second, we compared levels of attitudes toward convergence in terms of engineering education accreditation, gender and academic year. Third, latent classes, which were distinguished in terms of attitudes toward convergence, were identified. Participants were 2076 engineering students. By using factor analysis and Rasch analysis, validity and reliability of instrument measuring attitudes toward convergence were confirmed. The differences in attitude toward convergence in terms of engineering education accreditation experience, gender, and academic year were examined by independent t-test and ANOVA. There were significant differences in attitude towards convergence in terms of engineering education accreditation, gender, and academic year. Students who experience engineering education accreditation program and male and high academic year have higher levels of attitude toward convergence than others. Lastly latent class analysis (LCA) was conducted to identify subgroups underlying engineering students in terms of attitude toward convergence and five latent classes were identified. In addition, the chi-square results showed that there were significant relationships between identified latent classes and engineering education accreditation, gender, and academic year. Based on these results, engineering education considering students' characteristics and diversity in attitude toward convergence were discussed.

• 한국노년학
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• v.40 no.1
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• pp.33-49
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• 2020

This study was conducted to examine the latent classes in social exclusion and to analyse empirically the effects on the economic instability of old age by this type. And it also sought to look at whether the influence of old age anxiety varies with the subjective class consciousness of the elderly. Using the 14th data from the Korea General Social Survey (KGSS) in 2016, 1,041 adult males and females aged 18 years old were analyzed at the time of the survey. T-test, potential layer analysis (LCA), and multinomantic analysis of potential groups were conducted using the STATA14 and MPLUS 7 statistical programs. Finally, multi-regression analysis was performed to identify the moderate effect and effects among variables. According to the research, the types of social exclusion were three groups, followed by social exclusion group (49.3%), Multi-dimensional exclusion group (30.9%), and active social participation group (19.7%). The social exclusion group has the lowest possibility of economic, employment, and health exclusion, but the exclusion of formal and informal social activities seem to prominent, and the multi-dimensional exclusion group is more than 50% likely to experience exclusion in all areas. Active social participation are characterized by very active participation in informal social activities. By conducting multinominal logistic regression, it was observed that the social exclusion group included more young people than other groups, and that the multi-dimensional exclusion group included many elderly women without spouses. Finally, multiple regression analysis showed that social exclusion type interacts with subjective class consciousness and affects economic anxiety of old age.

• Journal of Science Education
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• v.41 no.1
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• pp.16-35
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• 2017

This study attempted to investigate the relationship among engineering students' creativity, engineering education accreditation, gender, and academic year. To be specific, fist, we examined the validity and reliability of the instrument for measuring engineering students' creativity by conducting Rasch analysis. Second, we compared level of creativity in terms of gender, academic year, and engineering education accreditation by using three-way ANOVA. Third, correlations among four constructs of creativity were examined. Fourth, latent classes with respect to creativity within the participants were identified using polytomous latent class analysis (poLCA). Data were collected from 2098 engineering students by using instrument for measuring four different constructs (creative cognition, creative tendency, collaboration, environment). By using Rasch analysis, validity and reliability of instrument for measuring creativity were confirmed. And the results of three-way ANOVA showed that there were significant difference in creativity in terms of gender. Female students showed the low level of creativity compared with male students. Also there were significant difference in creativity except creative cognition factor in terms of academic year. But there were no significant difference in creativity between students who participated engineering education accreditation program and the others. All constructs of creativity were significantly correlated with each others. Lastly, poLCA results showed that there were three distinct subgroups within engineering students in terms of the level of creativity. In the subgroup with low creativity, there were more female and first year students. Based on these findings, we discussed education for engineering students' creativity.

• Communications of Mathematical Education
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• v.34 no.4
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• pp.485-506
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• 2020

The purpose of this study is to analyze of the effect in Mathematics Teachers beliefs on their students beliefs by Latent Class Regression Model (LCRM). For this analysis, the study used the findings and surveys of Kang, Hong (2020) who developed a belief profile by analyzing the mathematical beliefs of 60 high school teachers and 1,850 second-year high school students learning from them through the Latent Class Analysis (LCA). As a result It was observed that 'Nature of Mathematics', 'Mathematic Teaching' and 'Mathematical Ability' of mathematics teachers beliefs influence the mathematical beliefs of students. The teacher's belief of 'Nature of Mathematics' statistically significant effects on students' beliefs in 'School Mathematics', 'Problem Solving', 'Mathematics Learning'. The teacher's belief of 'Teaching Mathematics', 'Mathematical Ability' statistically significant effects on students' beliefs in 'School Mathematics', 'Problem Solving', 'Self-Concept'. The results of this study can give a preview of the phenomenon in which teacher's mathematical beliefs are reproduced into student's mathematical beliefs. In addition, the results of observation of this study can be used to the contents that can achieve the purpose of reorientation for mathematics teachers.

• Journal of the Korea Convergence Society
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• v.11 no.1
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• pp.221-235
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• 2020

This study identified the latent groups according to smartphone addiction tendency and examined the factors affecting the latent group identification. The best-fitting LCA solution had three classes. The first group was 'non-academic stressed group, immersed in smartphone' It was characterized low scores on academic stress and average scores on smartphone addiction tendency. The second group was 'medium level academic stressed group, immersed in smartphone' which scored slightly above average in academic stress and smartphone addiction tendency. The third group was 'medium level academic stressed group, non-immersed in smartphone'. It showed higher scores than average in academic stress, but students with far lower scores in smartphone addiction tendency. Logistic analysis result showed that gender and grade were significant. This study is meaningful in analyzing academic related variable(academic stress) and mental health related variable(smartphone addiction tendency) to classify the groups according to patterns between the two variables and suggest appropriate intervention for each group in a convergence way.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.9
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• pp.482-491
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• 2018

This study intended to identify different level of teacher-efficacy, perception of principals' leadership and peer collaboration as it pertains to a teachers' job stress and job satisfaction in Elementary school. Samples include 1,031 teachers in elementary school from Korean Children & Youth Panel Survey(KCYPS) and data were analyzed using Latent Class Analysis(LCA) to identify different patterns of teacher-efficacy and perception of principals' leadership and peer collaboration. Multivariate analysis of variance were employed to identify the influence of predictors for classification of teachers' job stress and job satisfaction among latent classes. The study found three latent classes at risk class, middle-level adaptive class, and adaptive class and results showed that each distinctive class can be identified by some of predictors. Teachers at adaptive class showed higher teacher-efficacy and positive perception of principals' leadership and peer collaboration than teachers at risk and middle-level adaptive class. Also, teachers at adaptive class showed lower job stress and higher job satisfaction than teachers at two other classes. The study suggests that help teachers based on personal profile are effective rather teacher-efficacy and perception of principals' leadership and peer collaboration.

• Korean Journal of Culture and Social Issue
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• v.27 no.4
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• pp.561-584
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• 2021

This study was conducted to classify 601 Korean adults into latent classes according to their love types and identify the differences in depression and find variables that affect the latent classes classification. As a result of the latent class analysis, the latent group for love types of Korean adults were classified into the L-H (7.7%) group, which showed the highest level of all three factors of intimacy, passion, and commitment, and the L-MH (33.6%) group, which all three factors were higher than the average, the L-M (39.8%) group with the mean of all three factors, the L-ML (14.6%) group with all three factors lower than the mean, and the L-L (4.3%) group with the lowest all three factors. Also, as a result of ANOVA, the L-MH group was psychologically healthier and more adaptive than the L-ML group. As a result of multinomial logistic analysis, females were more likely to belong to L-M, L-ML and L-L groups than males. In addition, singles were more likely to belong to the L-M and L-ML groups than those who were married. Also, the higher the anxiety attachment level, the higher the likelihood of belonging to the L-M, L-ML, and L-L groups than the L-H and L-MH groups, the L-ML and L-L groups than the L-M groups, and the L-L group rather than the L-ML groups. However, age, neuroticism, and emotional regulation did not affect the classification of latent classes. This study is meaningful in that it identified the various latent classes for the love types of Korean adults more three-dimensionally and suggested the possibility of differential interventions according to the characteristics of each group.

• Korean Journal of Social Welfare Studies
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• v.48 no.3
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• pp.171-208
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• 2017

The purpose of this study is to classify the underlying and parsimonious types of child maltreatment and examine whether the effects of risk factors on child maltreatment recurrence differ by type of maltreatment. We utilized the multiyear national administrative data from the National Child Maltreatment Information System collected by Child Protection Agency in Korea. Of 26,921 child maltreatment victims reported and substantiated on or after January 1, 2012, 1,447 children who had recurrence of child maltreatment until December 31, 2015 were selected as maltreatment recurrence group and 4,580 children who had not experienced maltreatment since first substantiation were assigned as maltreatment non-recurrence group. Latent class analysis(LCA) and latent transition analysis(LTA) were used to group children with similar maltreatment subtypes into discrete classes of child maltreatment recurrence. Logistic regression is employed to examine the association between the child maltreatment predominant types and risk factors for recurrence. Results of LCA and LTA showed four latent classes representing predominant type of child maltreatment: 'physical abuse predominant type', 'emotional abuse predominant type', 'sexual abuse predominant type', and 'neglect type'. Significant differences in the effect of risk factors among latent classes were found in child's age and gender, perpetrator's gender, family poverty, biological parent as the perpetrator, domestic violence toward partner, perpetrator's alcoholic problem, insufficient parenting skills, and out-of-home care service, Based on these findings, results suggested how the typology can be used to guide decision about who to target in prevention and intervention programs, and which features of risk factors to target. Practice and policy implications as well as further research tasks were discussed in the lights of searching for useful and important strategies to prevent recurrence of child maltreatment.