• Title, Summary, Keyword: Structural Equation Modeling

### A Tutorial on Covariance-based Structural Equation Modeling using R: focused on "lavaan" Package (R을 이용한 공분산 기반 구조방정식 모델링 튜토리얼: Lavaan 패키지를 중심으로)

• Yoon, Cheol-Ho;Choi, Kwang-Don
• Journal of Digital Convergence
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• v.13 no.10
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• pp.121-133
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• 2015
• This tutorial presents an approach to perform the covariance based structural equation modeling using the R. For this purpose, the tutorial defines the criteria for the covariance based structural equation modeling by reviewing previous studies, and shows how to analyze the research model with an example using the "lavaan" which is the R package supporting the covariance based structural equation modeling. In this tutorial, a covariance-based structural equation modeling technique using the R and the R scripts targeting the example model were proposed as the results. This tutorial will be useful to start the study of the covariance based structural equation modeling for the researchers who first encounter the covariance based structural equation modeling and will provide the knowledge base for in-depth analysis through the covariance based structural equation modeling technique using R which is the integrated statistical software operating environment for the researchers familiar with the covariance based structural equation modeling.

### Structural Equation Modeling Using R: Analysis Procedure and Method (R을 이용한 구조방정식모델링: 분석절차 및 방법)

• Kwahk, Kee-Young
• Knowledge Management Research
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• v.20 no.1
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• pp.1-26
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• 2019
• This tutorial introduces procedures and methods for performing structural equation modeling using R. For this, we present the whole process of analyzing the structural equations model from the confirmatory factor analysis to the path diagram generation using the lavaan package, which is relatively well evaluated among the R packages supporting the structural equation modeling, together with the R program codes. Considering that research applying structural equation modeling techniques is the mainstream in a variety of social sciences, including business administration, and that there is growing interest in open source R, this tutorial focuses on researchers who are looking for alternatives to traditional commercial statistical packages and is expected that it will be a useful guidebook for them.

### Structural Equation Modeling Using R: Mediation/Moderation Effect Analysis and Multiple-Group Analysis (R을 이용한 구조방정식모델링: 매개효과분석/조절효과분석 및 다중집단분석)

• Kwahk, Kee-Young
• Knowledge Management Research
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• v.20 no.2
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• pp.1-24
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• 2019
• This tutorial introduces procedures and methods for performing structural equation modeling using R. To do this, we present advanced analysis methods based on structural equation model such as mediation effect analysis, moderation effect analysis, moderated mediation effect analysis, and multiple-group analysis with R program code using R lavaan package that supports structural equation modeling. R is flexible and scalable, unlike traditional commercial statistical packages. Therefore, new analytical techniques are likely to be implemented ahead of any other statistical package. From this point of view, R will be a very appropriate choice for applying new analytical techniques or advanced techniques that researchers need. Considering that various studies in the social sciences are applying structural equations modeling techniques and increasing interest in open source R, this tutorial is expected to be useful for researchers who are looking for alternatives to existing commercial statistical packages.

### A Mean of Structural equation modeling on AMOS Software (AMOS 소프트웨어에서 구현되는 구조방정식 모형과 의미)

• Kim, Kyung-Tae
• Proceedings of the Korean Association for Survey Research Conference
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• pp.55-65
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• 2007
• In this research, it will be examined on mathematical model of AMOS software program that ues for Covariance Structure Analysis. if we have not understood to mathematical model of Covariance Structure, we fail to understand Structural equation modeling. Similarly If We were not understand to mathematical model of AMOS Software, we do not use Software adequately. Therefore we examine two sorts of Software that be designed for Structural equation modeling or Covariance Structure Analysis. In this research, We will focus on 8 assumption of Structural equation modeling and compare AMOS(Analysis of MOment Structure) program with LISREL(Linear Structure RELation) program. We found that A Program of AMOS Software have materialized with RAM(Reticular Action Model).

### Customer satisfaction and competitiveness in Global Company: Structural Equation Modeling(SEM) approach to identify the role quality factor (글로벌 기업의 고객만족과 경쟁력 모델 구축: 품질요인확인을 위한 구조방정식모델 적용)

• Kim, Gye Soo;Park, Jong Cheol
• Journal of the Korean Society for Quality Management
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• v.43 no.1
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• pp.43-56
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• 2015
• Purpose: In this research, We made the conceptual frameworks for SEM(Structural Equation Modeling) on Global quality's origin and empirical research. Developing conceptual frameworks is an important step in theory building and theory testing. This research model was developed by strong theoretical foundation which is quality and systematical model. Methods: Questionnaire was developed, and data was collected and analyzed for this study. The analysis was conducted using SEM(Structural Equation Modeling). Results: Results show that process quality and interaction quality are important drivers in customer satisfaction. Customer satisfaction is strongly impact on customer loyalty(repeated purchase). Conclusion: In turbulent business era, Global company require not only excellent quality but also create customer oriented culture and control over operation in the foreign country.

### A Tutorial on PLS Structural Equating Modeling using R: (Centering on) Exemplified Research Model and Data (R을 이용한 PLS 구조방정식모형 분석 튜토리얼: 예시 연구모형 및 데이터를 중심으로)

• Yoon, Cheolho;Kim, Sanghoon
• Information Systems Review
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• v.16 no.3
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• pp.89-112
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• 2014
• This tutorial presents an approach to perform the PLS structural equation modeling using the R. For this purpose, the practical guide defines the criteria for the PLS structural equation modeling by reviewing previous studies, and shows how to analyze the research model with an example using the "plspm" which is the R package for the performing PLS path analysis against the criteria. This practical guide will be useful for the study of the PLS model analysis for new researchers and will provide the knowledge base for in-depth analysis through the new PLS structural equation modeling technique using R which is the integrated statistical software operating environment for the researchers familiar with the PLS structural equation modeling.

### A Study on the Structural Equation Modeling of the Relationships among Major Satisfaction, Career Search Efficacy, and Career Exploration Behavior with Marine Science High School Students (수산해양계열 고등학생의 전공만족, 진로탐색 자기효능감 및 진로탐색행동의 구조적 관계 연구)

• Heo, Gyun
• Journal of Fisheries and Marine Sciences Education
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• v.25 no.6
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• pp.1306-1314
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• 2013
• The purpose of this study is to find the structural relationships among major satisfaction, career search efficacy, and career exploration behavior with marine science high school students. For investigating this topic, 524 students were surveyed from the marine science high schools. In order to find out the structural relationships among major satisfaction, career search efficacy, and career exploration behavior, structural equation modeling was used. Followings were the results of the research: (a) Major satisfaction effected significantly on the career search efficacy. (b) Career search efficacy effected significantly on the career exploration behavior. (C) There was not significant direct cause and effects from major satisfaction to career exploration behavior, but indirect effect was significant. Some recommendations were suggested for increasing career exploration behavior of marine science high school students.

### The Structural Equation Modeling in MIS : The Perspectives of Lisrel and PLS Applications (경영정보학 분야의 구조방정식모형 적용분석 : Lisrel과 PLS 방법을 중심으로)

• Kim, In-Jai;Min, Geum-Young;Shim, Hyoung-Seop
• Journal of Information Technology Services
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• v.10 no.2
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• pp.203-221
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• 2011
• The purpose of this study is to investigate the applications of Structural Equation Modeling(SEM) into MIS area in recent years. Two methodologies, Lisrel and PLS, are adopted for the method comparison. A research model, based upon TAM(Technology Acceptance Model) is used for the analysis of the data set of a previous study. The research model includes six research variables that are composed of twenty-eight question items. 272 data are used for data analyses through Lisrel v.8.72 and Visual PLS v.1.04. This study shows the statistical results of Lisrel are the same to those of PLS. The contribution of this study can be suggested as the followings; (1) A theoretical comparison of two methodologies is shown, (2) A statistical analysis is done at a real-situated data set, and (3) Several implications are suggested.

### Using Structural Equation Modeling to Fit a Model of Student Background, Teacher Background, Home Environment, and a School Characteristic to Mathematics Achievement on the TIMSS

• Cho, Gyu-Pan
• Research in Mathematical Education
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• v.7 no.4
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• pp.247-270
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• 2003
• The purpose of this study is to build a model that explains the relationship between and among five variables that are student background, teacher background, home environment, school characteristic, and student mathematics achievement, using structural equation modeling. Another purpose of this study is to compare the relationships of these variables between the United States and Korea in 7th and 8th grades mathematics. Student, teacher, and school background files from population 2 in the TIMSS were selected for this study. The result of the study provides practical information for teachers, parents, school principals, and other people who are interested in improving student achievement, and also provides the information that may explain differences and similarities between the US and Korea in mathematics achievement.

### A Comparison Analysis among Structural Equation Modeling (AMOS, LISREL and PLS) using the Same Data (동일 데이터를 이용한 구조방정식(AMOS, LISREL and PLS) 툴 간의 비교분석)

• Nam, Soo-tai;Kim, Do-goan;Jin, Chan-yong
• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• pp.131-134
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• 2018
• Structural equation modeling is pointing to statistical procedures that simultaneously perform path analysis and confirmatory factor analysis. Today, this statistical procedure is an essential tool for researchers in the social sciences. There are as (AMOS, LISREL and PLS) representative tools that can perform structural equation modeling analysis. AMOS provides a convenient graphical user interface for beginners to use. PLS has the advantage of not having a constraint on normal distribution as well as a graphical user interface. Therefore, we compared and analyzed the three most commonly used tools in social sciences. This study suggests practical and theoretical implications based on the results.