Literature DB >> 35185157

A Comparison of Reliability Estimation Based on Confirmatory Factor Analysis and Exploratory Structural Equation Models.

Yuanshu Fu1,2, Zhonglin Wen2, Yang Wang3.   

Abstract

Composite reliability, or coefficient omega, can be estimated using structural equation modeling. Composite reliability is usually estimated under the basic independent clusters model of confirmatory factor analysis (ICM-CFA). However, due to the existence of cross-loadings, the model fit of the exploratory structural equation model (ESEM) is often found to be substantially better than that of ICM-CFA. The present study first illustrated the method used to estimate composite reliability under ESEM and then compared the difference between ESEM and ICM-CFA in terms of composite reliability estimation under various indicators per factor, target factor loadings, cross-loadings, and sample sizes. The results showed no apparent difference in using ESEM or ICM-CFA for estimating composite reliability, and the rotation type did not affect the composite reliability estimates generated by ESEM. An empirical example was given as further proof of the results of the simulation studies. Based on the present study, we suggest that if the model fit of ESEM (regardless of the utilized rotation criteria) is acceptable but that of ICM-CFA is not, the composite reliability estimates based on the above two models should be similar. If the target factor loadings are relatively small, researchers should increase the number of indicators per factor or increase the sample size.
© The Author(s) 2021.

Entities:  

Keywords:  composite reliability; confirmatory factor analysis; exploratory structural equation modeling

Year:  2021        PMID: 35185157      PMCID: PMC8850766          DOI: 10.1177/00131644211008953

Source DB:  PubMed          Journal:  Educ Psychol Meas        ISSN: 0013-1644            Impact factor:   2.821


  13 in total

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Review 8.  Exploratory structural equation modeling: an integration of the best features of exploratory and confirmatory factor analysis.

Authors:  Herbert W Marsh; Alexandre J S Morin; Philip D Parker; Gurvinder Kaur
Journal:  Annu Rev Clin Psychol       Date:  2013-12-02       Impact factor: 18.561

9.  Bayesian mediation analysis.

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Journal:  Child Dev       Date:  2007 Sep-Oct
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