• 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.

• 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.

• 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).

• International conference on construction engineering and project management
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• 2007.03a
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• pp.653-661
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• 2007

Overseas construction projects tend to be more complex than domestic projects, being exposed to more external risks, such as politics, economy, society, and culture, as well as more internal risks from the project itself. It is crucial to have an early understanding of the project condition, in order to be well prepared in various phases of the project. This study compares a structural equation model and multiple regression analysis, in their capacity to predict cost performance of international construction projects. The structural equation model shows a more accurate prediction of cost performance than does regression analysis, due to its intrinsic capability of considering various cost factors in a systematic way.

• 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.

• The Mathematical Education
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• v.56 no.4
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• pp.407-434
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• 2017

The purpose of this study is to develop and verify the TPACK measurement tool for middle and high school mathematics teachers in the Korean context. Also, by clarifying the relationship between subordinate factors of Mathematics teachers' TPACK, an attempt was made to provide suggestions on the designs and directions for the in-service and pre-service teacher education and the programs for improving mathematics teachers' TPACK in the future. In order to achieve this goal, TPACK factors of mathematics teachers were extracted by reviewing literature on PCK, MKT, and TPACK. Then, content validity, basic statistical survey, reliability verification, exploratory factor analysis, confirmatory factor analysis, and structural equation model verification were conducted sequentially. At first, preliminary analysis was carried out on 79 mathematics teachers, and 76 items excluding the items with extreme value and reliability were included in the basic statistical analysis. And secondly, an exploratory factor analysis was conducted on 376 mathematics teachers, and this instrument consisted of 7 subordinate factors(CK, PK, TK, PCK, TCK, TPK, TPACK) and 61 items. Also by conducting confirmatory factor analysis and structural equation model test with 254 mathematics teachers, the measurement tool was confirmed the validity and reliability through statistically significant analysis. Then, the importance of integrated knowledge was confirmed by looking at the relationship between the TPACK factors of in-service mathematics teachers. The integrated knowledge(PCK, TCK, TPK) has played a crucial role in the formation of TPACK rather than the knowledge of CK, PK, and TK alone. Finally, the validity of TCK was confirmed through the structural equation modeling of TPACK. TCK not only directly affected TPACK, but also indirectly through TPK. According to these affirmative results, this measurement tool is claimed to be suitable for measuring the factors of Mathematics teachers' TPACK, and also the structural equation model can be regarded as a suitable model for analyzing the structural relationship of mathematics teachers' TPACK.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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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.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.387-394
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• 2004

In the structural analysis procedure using finite element technique, the performance of a linear equation solver is critical because the linear equation solving part spends most of the computing time for finite element analysis codes. However, most of researchers are still using inefficient profile-based direct solvers such as the band solver or the skyline solver. In this research, we introduce the multifrontal solution method as an efficient direct solution method for structural analysis, and show the efficiency and performance of the multifrontal solution method by comparing the performance of our own implementation of the multifrontal method with the band solver or the skyline solver. In addition, we also compare the performance of our solver with other implementations of the multifrontal method such as WSMP and MUMPS as well as commercial structural analysis packages such as ABAQUS and NASTRAN. Through the performance test results, the usefulness and efficiency of our domain-wise multifrontal solver for structural analysis is shown.

• 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.

• 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.