• Title/Summary/Keyword: Latent Profile Analysis

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A multivariate latent class profile analysis for longitudinal data with a latent group variable

  • Lee, Jung Wun;Chung, Hwan
    • Communications for Statistical Applications and Methods
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    • v.27 no.1
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    • pp.15-35
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    • 2020
  • In research on behavioral studies, significant attention has been paid to the stage-sequential process for multiple latent class variables. We now explore the stage-sequential process of multiple latent class variables using the multivariate latent class profile analysis (MLCPA). A latent profile variable, representing the stage-sequential process in MLCPA, is formed by a set of repeatedly measured categorical response variables. This paper proposes the extended MLCPA in order to explain an association between the latent profile variable and the latent group variable as a form of a two-dimensional contingency table. We applied the extended MLCPA to the National Longitudinal Survey on Youth 1997 (NLSY97) data to investigate the association between of developmental progression of depression and substance use behaviors among adolescents who experienced Authoritarian parental styles in their youth.

Latent Profile Analysis of High School Students' Fire Safety Awareness

  • Lee, Soon-Beom;Kim, Eun-Mi;Kong, Ha-Sung
    • International journal of advanced smart convergence
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    • v.10 no.4
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    • pp.124-133
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    • 2021
  • The purpose of this study is to analyze the types of latent profiles of high school students' fire safety awareness and to identify the characteristics of related variables. For this purpose, a survey was conducted from March 22 to May 25, 2021 for 1054 high school students (male; 569, female; 485) in 3 cities, in Jeollabuk-do. The latent profile was analyzed using a scale consisting of 4 sub-factors: 'fire prevention', 'fire preparedness', 'indirect fire response', and 'direct fire response'. It was checked whether there were differences according to the inter-individual differences of the latent group. As a result of the analysis, fire safety awareness of high school students was classified into three latent profiles. The three groups were named 'High Perception Type', 'Moderate Perception Type', and 'Low Perception Type' according to their types. In fire safety awareness, there is a significant difference in the individual differences according to the gender and academic achievement of the latent profile. These results are meaningful as the first study to analyze the latent profile of high school students' fire safety awareness, and it is also meaningful to provide a useful basis for the contents and methods of customized fire safety education by identifying the tendencies of spontaneous groups and their fire safety awareness.

Latent Profile Analysis According to the Subject Selection Criteria of General High School Students

  • Kim, Eun-Mi
    • International Journal of Advanced Culture Technology
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    • v.9 no.4
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    • pp.226-236
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    • 2021
  • The purpose of this study is to analyze the type of latent profile for general high school students' subject selection criteria and to identify the characteristics of the latent class. The survey data of 1072 general high school students (male; 648, female; 424) in G city, Jeollabuk-do and the scale composed of 8 sub-factors: 'SAT orientation', 'academic achievement', 'ability orientation', 'pursuit of interest', 'teacher orientation', 'career development', 'others' recommendation', and 'subject availability' were used for latent profile analysis and cross-analysis between potential layers. As a result of the analysis, high school students' perceptions of subject selection were classified into four latent profiles. The four groups were named 'High Perception Type', 'Low Perception Type', 'Self-Directed Type', and 'Stability-Oriented Type' according to their types. It was found that there was a difference between the latent classes in the importance and performance level of the subject selection criteria. These results can help identify the subject selection tendencies of latent groups in the operation of the 2015 revised curriculum and the 2025 high school credit system that emphasizes the student-centered course selection curriculum and they can also provide customized course selection guidance considering individual differences.

Predicting Longitudinal Patterns of Emotional and Behavioral Problems in Early Adolescence : A Latent Class and Latent Transition Analysis (초기 청소년기 정서행동문제의 종단적 변화에 따른 잠재프로파일 분류 및 전이 영향요인 분석)

  • Kim, Bitna;Jang, Hyein;Park, Ju Hee
    • Human Ecology Research
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    • v.60 no.1
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    • pp.53-68
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    • 2022
  • Using a person-centered approach, the current study investigated latent profiles for the emotional and behavioral problems of students in sixth-grade in elementary school and second grade of middle school. The aim was to explore latent transition patterns and verify the factors affecting the transitions. The participants were 1,937 adolescents who responded to the 3rd year (6th grade of elementary school; Time 1), 4th year (1st grade of middle school), and 5th year (2nd grade of middle school; Time 2) of the Korean Children Youth Panel Study. Latent profile and latent transition analyses were performed. The results were as follows: first, the latent profile of emotional and behavioral problems changed from Time 1 to Time 2. The latent groups at Time 1 were classified into low, moderate, high, and externalizing-dominant, whereas at Time 2, five groups were identified: low, moderate, high, externalizing-dominant, and withdrawal-dominant. Second, transition analyses revealed that although 22.3-57.0% of latent groups remained unchanged, there were significant changes over time between groups, as a new group ('withdrawal-dominant') emerged in Time 2. Third, different factors influenced the latent profile transition of emotional and behavioral problems depending on the transition pattern. Higher levels of self-esteem, better relationships with peers and teachers, and lower levels of parental inconsistency meant emotional and behavioral problems had not worsened at Time 2. The results suggest that early interventions are needed during the transition from childhood to early adolescence.

Joint latent class analysis for longitudinal data: an application on adolescent emotional well-being

  • Kim, Eun Ah;Chung, Hwan;Jeon, Saebom
    • Communications for Statistical Applications and Methods
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    • v.27 no.2
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    • pp.241-254
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    • 2020
  • This study proposes generalized models of joint latent class analysis (JLCA) for longitudinal data in two approaches, a JLCA with latent profile (JLCPA) and a JLCA with latent transition (JLTA). Our models reflect cross-sectional as well as longitudinal dependence among multiple latent classes and track multiple class-sequences over time. For the identifiability and meaningful inference, EM algorithm produces maximum-likelihood estimates under local independence assumptions. As an empirical analysis, we apply our models to track the joint patterns of adolescent depression and anxiety among US adolescents and show that both JLCPA and JLTA identify three adolescent emotional well-being subgroups. In addition, JLCPA classifies two representative profiles for these emotional well-being subgroups across time, and these profiles have different tendencies according to the parent-adolescent-relationship subgroups.

Investigating Students' Profiles of Mathematical Modeling: A Latent Profile Analysis in PISA 2012

  • SeoJin Jeong;Jihyun Hwang;Jeong Su Ahn
    • Research in Mathematical Education
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    • v.26 no.3
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    • pp.235-252
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    • 2023
  • We investigated the classification of learner groups for students' mathematical modeling competency and analyzed the characteristics in each profile group for each country and variable using PISA 2012 data from six countries. With a perspective on measuring sub-competency, we applied the latent profile analysis method to student achievement for mathematical modeling variables - Formulate, Employ, Interpret. The findings showed the presence of 4-6 profile groups, with the variables exhibiting high and low achievement within each profile group varying by country, and a hierarchical structure was observed in the profile group distribution in all countries, interestingly, the Formulate variable showed the largest difference between high-achieving and low-achieving profile groups. These results have significant implications. Comparison by country, variable, and profile group can provide valuable insights into understanding the various characteristics of students' mathematical modeling competency. The Formulate variable could serve as the most suitable predictor of a student's profile group and the score range of other variables. We suggest further studies to gain more detailed insights into mathematical modeling competency with different cultural contexts.

Analysis of Latent profiles and Inter-individual Differences in Disaster Safety Awareness of High school

  • Lee, Soon-Beom;Kim, Eun-Mi;Kong, Ha-Sung
    • International Journal of Internet, Broadcasting and Communication
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    • v.14 no.2
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    • pp.171-182
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    • 2022
  • In this study, by classifying latent groups for disaster safety awareness focusing on the four sub-factors of the developed disaster awareness scale of high school students, the characteristics of each group were examined, and the differences between latent classes according to inter-individual differences were investigated. As a result of analysis based on the data of a total of 1054 high school students, the disaster safety awareness of high school students was classified into three latent groups. Each latent group was named 'High Safety Awareness Type(SAT)', 'Normal SAT', and 'Low SAT' according to its characteristics. In all four fire safety awareness sub-factors, 'High SAT', which had a high score, accounted for 56.5% of the total, and 'Normal SAT', which had a moderate score in the sub-factors, had the lowest ratio at 20.3%. There were no significant differences by gender, grade, and academic achievement of the latent group. These results are not only meaningful as the first study of the latent profile analysis of high school students on disaster safety awareness, but also help to identify the characteristics of individuals in each latent group with more subdivisions and provide useful data for disaster safety awareness education according to individual differences. The implications of this study and suggestions for follow-up studies were discussed.

Can Data-Driven Analysis Demonstrate the Plausibility of Traditional Medical Typology?

  • Chae, Han;Lee, Siwoo;Lee, Soo Jin
    • Journal of Oriental Neuropsychiatry
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    • v.32 no.4
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    • pp.303-320
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    • 2021
  • Objectives: Although medical typologies based on indigenous biopsychological ideas have been described, their integrity has been questioned due to its theory-driven nature in categorization. Therefore, studies on the Sasang typology, a temperament-based traditional Korean medicine, are needed to examine whether it is possible to classify types of specific biopsychological profiles using data-driven analysis. Methods: Psychological measures of the Eastern Sasang Personality Questionnaire (SPQ) and Western NEO-Personality Inventory (NEO-PI) along with physical measures and Sasang types were acquired from 2,049 participants. Latent groups based on the SPQ and NEO-PI subscale scores were extracted using Latent Profile Analysis. Their psychosomatic features were then compared with those of Sasang types. Results: Three SPQ-based latent groups showed distinctive psychological and physical features consistent with those of Sasang types. However, four NEOPI-based latent groups presented only psychological features. Furthermore, SPQ-High and SPQ-Low latent groups demonstrated similar psychosomatic profiles to those of So-Yang and So-Eum Sasang types, respectively. Conclusions: This study illustrates that biopsychological profiles of Sasang types are supported by psychosomatic features of latent groups based on SPQ of Eastern psychology, signifying that the categorization of Sasang typology have acceptable validity and reliability.

An Exploratory Study of Psychological and Biosocial Variables Based in the Latent Profile Analysis of Temperament and Character among College Student (대학생의 기질 및 성격 잠재 프로파일에 따른 심리 및 생물사회적 변인의 탐색적 연구)

  • Jeong, Su Dong;Lee, Soo Jin
    • The Journal of the Korea Contents Association
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    • v.22 no.3
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    • pp.165-178
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    • 2022
  • In this study, to explore the psychological and biosocial characteristics of the temperament and character's latent profile group, first, the latent group was identified with the seven variables of the Temperament and Character Inventory(TCI), and second, the difference between the psychological and biosocial characteristics of three identified latent groups. A total of 287 university students participated, and the latent groups was identified through latent profile analysis, a human-centeted statistical method, using Cloninger's TCI, Cognitive Emotion Regulation Questionnaire(CERQ), Positive Affect and Negative Affect Schedule(PANAS), Composite Scale of Moriningness(CSM), Pittsburgh Sleep Qulity Index(PSQI), and Satisfaction With Life Scale(SWLS). As result, first, three latent groups were identified through latent profile analysis using the seven variables of TCI. second, significant differences were identified in CERQ, PANAS, which are psychological variables, CSM, PSQI, and SWLS, which are biosocial variables among the latent groups. In conclusion, the importance of Self-Directedness(SD), a character factor that can be developed rather than Harm-Avoidance(HA), a temperament factor from nature, was confirmed. And the necessity of follow-up studies on psychological and biosocial variables for adaptive and mature personality was discussed.

A latent profile analysis of perceptions about Mathematics teachers in school lessons (학교수업에서 수학교사에 대한 인식의 잠재프로파일 분석)

  • Ko, Dong Hyun;Jung, Hee Sun
    • The Mathematical Education
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    • v.57 no.2
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    • pp.75-92
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    • 2018
  • Based on Perceptions about Mathematics Teachers (PMT) perceived by high school students, measured by 2189 students from Seoul Educational Longitudinal Study 2014 (SELS 2014), latent profile analysis (LPA) identified five distinct types of student groups (positive, partial positive, middle, negative, extreme negative). These student of positive, middle, and negative groups are positive, moderate and negative perceptions about math teachers. Partial positive group generally had a positive perception about mathematics teachers, extremely negative group was very negative about mathematics teachers. Both of these groups had peculiarly inconsistent trends and several anomalies. The Multinomial logistic regression analyses also indicated that individual factors (gender, major, self-concept, resilience, self-assessment, career maturity), school factors (friendship, relationship with school teachers) and parental factors (academic-relationship, emotional-relationship) were significant predictors of PMT profile groups. The Analysis of variance also indicated that mathematics class (attitude, satisfaction and atmosphere), Mathematics achievement were significant predictors of PMT profile groups. The profiling of perceptions about mathematics teachers resulted in enhanced understanding of the complex range of processes students employed. During mathematics class, implementation of smooth interactions and communications between students and teachers added in the teaching and learning of mathematics.