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Construct Validity of Likert Scales through Confirmatory Factor Analysis: A Simulation Study Comparing Different Methods of Estimation Based on Pearson and Polychoric Correlations

International Journal of Social Science Studies

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Title Construct Validity of Likert Scales through Confirmatory Factor Analysis: A Simulation Study Comparing Different Methods of Estimation Based on Pearson and Polychoric Correlations
 
Creator Morata-Ramírez, María de los Ángeles
Holgado-Tello, Francisco Pablo
 
Description The widespread use of Pearson correlations and, by extension, the Maximum Likelihood estimation method, does not take into account the measurement properties of Likert scales observed variables when carrying out a construct validity process through Confirmatory Factor Analysis (CFA). This simulation study compares four estimation methods (Maximum Likelihood –ML-, Robust Maximum Likelihood –RML-, Robust Unweighted Least Squares –, RULS) according to two of the assumptions CFA is supposed to fulfil: multivariate normality and, especially, the continuous measurement nature of both latent and observed variables. Goodness of fit is diagnosed by X2 Likelihood Ratio Test and RMSEA indices. Results suggest ULS and RULS are preferable as polychoric correlations help to overcome grouping and transformation errors produced when using Pearson correlations for ordinal observed variables. Data measurement scale consideration enhances the ability of hypothesized models to reproduce accurately construct variables relationships.
 
Publisher Redfame Publishing
 
Contributor —
 
Date 2013-01-15
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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Format application/pdf
 
Identifier http://redfame.com/journal/index.php/ijsss/article/view/27
10.11114/ijsss.v1i1.27
 
Source International Journal of Social Science Studies; Vol 1, No 1 (2013); p54-61
2324-8041
2324-8033
 
Language eng
 
Relation http://redfame.com/journal/index.php/ijsss/article/view/27/29