Factor Analysis with Ordinal Indicators: A Monte Carlo Study Comparing DWLS and ULS Estimation

Factor analysis models with ordinal indicators are often estimated using a 3-stage procedure where the last stage involves obtaining parameter estimates by least squares from the sample polychoric correlations. A simulation study involving 324 conditions (1,000 replications per condition) was perfor...

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Bibliographic Details
Published in:Structural equation modeling 2009-10, Vol.16 (4), p.625-641
Main Authors: Forero, Carlos G., Maydeu-Olivares, Alberto, Gallardo-Pujol, David
Format: Article
Language:English
Subjects:
Comparative Analysis
Computation
Convergence
Correlation analysis
Discriminant analysis
Error of Measurement
Factor Analysis
Least Squares Statistics
Monte Carlo Methods
Monte Carlo simulation
Parameter estimation
Statistical Bias
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Summary:Factor analysis models with ordinal indicators are often estimated using a 3-stage procedure where the last stage involves obtaining parameter estimates by least squares from the sample polychoric correlations. A simulation study involving 324 conditions (1,000 replications per condition) was performed to compare the performance of diagonally weighted least squares (DWLS) and unweighted least squares (ULS) in the procedure's third stage. Overall, both methods provided accurate and similar results. However, ULS was found to provide more accurate and less variable parameter estimates, as well as more precise standard errors and better coverage rates. Nevertheless, convergence rates for DWLS are higher. Our recommendation is therefore to use ULS, and, in the case of nonconvergence, to use DWLS, as this method might converge when ULS does not.
ISSN:1070-5511
1532-8007
DOI:10.1080/10705510903203573