• 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.

• 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.

• 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.

• Perspectives in Nursing Science
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• v.11 no.2
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• pp.109-122
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• 2014

Purpose: The purpose of this study was to review research papers on structural equation models for hospital nurses' turnover intentions, and to identify the factors that influence these intentions. Methods: Twenty-four research papers on structural equation models for hospital nurses' turnover intentions were identified for systematic review. Results: All 24 papers assessed nurses' turnover intentions in general hospitals and university hospitals. A total of 36 indicators and 105 items were used to measure turnover intention. Turnover intention was positively related with 10 variables, and negatively with 17 variables. Organizational commitment, job satisfaction, job stress, burnout, organizational culture, and empowerment were found to have significant direct and indirect effects on nurses' turnover intentions. Structural equation models in 23 of the 24 research papers showed high compatibility with the data. The models accounted for 20.1% 68.0% of total variances. Conclusion: The study findings show recent trends in nurses' turnover intentions, and indicate directions for future research.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.2
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• pp.87-93
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• 2010

The partial least squares (PLS) method is popularly used for estimating the structural equation model, but the existing algorithm may not be directly implemented when probabilities are involved in some constructs or manifest variables. We propose a structural equation model including the brand choice as one construct having brand choice probabilities as its manifest variables. Then, we develop a PLS-based algorithm for the structural equation model by utilizing the multinomial logit model. A case is introduced as an application and simulation studies are performed to validate the proposed algorithm.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1223-1230
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• 2009

In the construction industry, Case-Based Reasoning (CBR) is considered to be the most suitable approach and determining the attribute weights is an important CBR problem. In this paper, a method is proposed for determining attribute weights that are calculated with attribute relation. The basic items of consideration were qualitative and quantitative influence factors. These quantitative factors were related to the qualitative factors to develop a Cost Drivers-structural equation model which can be used to estimate construction cost by considering attribute weight. The process of determining the attribute weight-structural equation model consists o 4 phases: selecting the predominant Cost Drivers for the SEM, applying the Cost Driers in the SEM, determining and verifying the attribute weights and deriving the Cost Estimation Equation. This study develops a cost estimating technique that complements the CBR method with a Cost Drivers-structural equation model which can be actively used during the schematic estimating phases of construction.

• International Journal of Highway Engineering
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• v.16 no.2
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• pp.107-118
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• 2014

PURPOSES : The purpose of study is to come up with ideas to improve both the use of the public bicycle and the practicality of the public bicycle system as well. METHODS : The study carried out an analysis on factors which would influence user's satisfaction by using a structural equation and then, discussed what the current public bicycle system should do to make improvements of its own. In order to Satisfaction of the public bicycle system("Tashu") in Daejeon city survey was conducted users and was based on statistical analysis SPSS 20 program, structural equation modeling program AMOS 20 was used for analysis. In addition, the reliability and validity of each question was conducted verification, to verify the hypothesis using structural equation model. RESULTS : According to the results of the analysis with the structural equation used, the connectivity, the convenience, the economic efficiency and the reliability in order were observed to have an influence on the satisfaction of the users CONCLUSIONS : The connectivity turned out to be a factor that would have the greatest concern with the satisfaction of the users. This finding was, therefore, interpreted that people who would ride the public bicycles understand them as more of a transit system that would take them, the people themselves, to another transfer rather than as some immediate transit system.

• Korean Journal of Human Ecology
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• v.16 no.1
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• pp.159-171
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• 2007

The purpose of this research is to analyze the difference of Structural Equation Model which shows the path between BRQ and its performance variables according to purchase product types-fashion brand types, clothing item groups. The subjects were women in their 20s to 40s living in Seoul and Metropolitan areas, and 482 copies of questionnaire were analyzed. Multi-Group Analysis of AMOS 5.0 Package was used to investigate structural equation model according to fashion brand types and clothing item groups. The results of this study were as follows. As for fashion brand types, there appeared to be significant differences between high price brand type and medium-low price brand type for three paths, namely brand satisfaction to brand loyalty, BRQ to brand attitude, and brand attitude to brand loyalty. However the verification of structural equation model according to clothing item groups showed no significant differences between formal wear and informal wear. Consequently, BRQ was proved to affect brand satisfaction and brand loyalty, and brand satisfaction was the important intermediate variable between BRQ and brand loyalty. As consumers were likely to show the difference of structural equation model according to the price of purchase goods, differencial marketing strategy would be suggested.

• Proceedings of the Korean Association for Survey Research Conference
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• 2007.11a
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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).

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1989.10a
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• pp.46-50
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• 1989

Methods for the estimation of the coefficient matrices in the equation of motion for a linear multi-degree-of-freedom structure arc studied. For this purpose, the equation of motion is transformed into an auto-regressive and moving average with auxiliary input (ARMAX) model. The ARMAX parameters are evaluated using several methods of parameter estimation; such as toe least squares, the instrumental variable, the maximum likelihood and the limited Information maximum likelihood methods. Then the parameters of the equation of motion are recovered therefrom. Numerical example is given for a 3-story building model subjected to an earthquake exitation.