Applied Mathematics and Physics
ISSN (Print): 2333-4878 ISSN (Online): 2333-4886 Website: http://www.sciepub.com/journal/amp Editor-in-chief: Vishwa Nath Maurya
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Applied Mathematics and Physics. 2017, 5(3), 85-94
DOI: 10.12691/amp-5-3-2
Open AccessArticle

A Review of Software Packages for Structural Equation Modeling: A Comparative Study

Ahmed A. El-Sheikh1, Mohamed R. Abonazel1, and Noha Gamil1

1Department of Applied Statistics and Econometrics, Institute of Statistical Studies and Research, Cairo University, Egypt

Pub. Date: August 04, 2017

Cite this paper:
Ahmed A. El-Sheikh, Mohamed R. Abonazel and Noha Gamil. A Review of Software Packages for Structural Equation Modeling: A Comparative Study. Applied Mathematics and Physics. 2017; 5(3):85-94. doi: 10.12691/amp-5-3-2

Abstract

Structural equation modeling (SEM) is a widely used statistical method in most of social science fields. Similar to other statistical methods, the choice of the appropriate estimation methods affects the results of the analysis, thus it was of importance to review some of SEM software packages and the availability of different estimation methods in these packages. Therefore, in this paper five SEM software packages (AMOS, LISREL, and three packages in R) dealing with SEM analysis were reviewed to guide the researcher about the usage of each package. Moreover, an empirical study was presented to assess the performance of different estimation methods under the existence of missing data. The results showed that full information maximum likelihood (FIML) was the best estimation method to deal with different missingness rates.

Keywords:
AMOS Confirmatory factor analysis Goodness-of-fit indexes LISREL Missing data analysis R software

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