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     Research Journal of Applied Sciences, Engineering and Technology


An Overview on R Packages for Structural Equation Modeling

1Haibin Qiu, 2Yanan Song and 1Tingdi Zhao
1School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China
2Department of Industrial Engineering, Tsinghua University, Beijing 100084, China
Research Journal of Applied Sciences, Engineering and Technology  2014  20:4182-4186
http://dx.doi.org/10.19026/rjaset.7.785  |  © The Author(s) 2014
Received: June 28, 2012  |  Accepted: August 28, 2012  |  Published: May 20, 2014

Abstract

The aim of this study is to present overview on R packages for structural equation modeling. Structural equation modeling, a statistical technique for testing and estimating causal relations using an amalgamation of statistical data and qualitative causal hypotheses, allow both confirmatory and exploratory modeling, meaning they are matched to both hypothesis testing and theory development. R project or R language, a free and popular programming language and computer software surroundings for statistical computing and graphics, is popularly used among statisticians for developing statistical computer software and data analysis. The major finding is that it is necessary to build excellent and enough structural equation modeling packages for R users to do research. Numerous packages for structural equation modeling of R project are introduced in this study and most of them are enclosed in the Comprehensive R Archive Network task view Psychometrics.

Keywords:

Psychometrics, R project, structural equation modeling,


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Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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