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Comparative Analysis3
Factor Analysis3
Item Response Theory3
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Structural Equation Modeling3
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Joreskog, Karl G.1
Mavridis, Dimitris1
Moustaki, Irini1
Smith, Richard M.1
Wright, Benjamin D.1
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A Comparison of Methods for Determining Dimensionality in Rasch Measurement.
Peer reviewed Peer reviewed
Smith, Richard M. – Structural Equation Modeling, 1996
The Rasch item fit approach for detecting multidimensionality in response data is compared with principal component analysis without rotation using simulated data. Results indicate that both approaches work in a variety of multidimensional data structures, but the Rasch item fit is better under some circumstances, as discussed. (SLD)
Descriptors: Comparative Analysis, Factor Analysis, Factor Structure, Goodness of Fit
Comparing Rasch Measurement and Factor Analysis.
Peer reviewed Peer reviewed
Wright, Benjamin D. – Structural Equation Modeling, 1996
Rasch measurement is preferable to factor analysis for reducing complex data matrices to unidimensional variables because factor analysis can mistake ordinally labeled stochastic observations for linear measures, and it does not construct linear measurement. Guidelines and instructions on how to use Rasch measurement to replace factor analysis are…
Descriptors: Comparative Analysis, Factor Analysis, Item Response Theory, Matrices
Factor Models for Ordinal Variables With Covariate Effects on the Manifest and Latent Variables: A Comparison of LISREL and IRT Approaches
Peer reviewed Peer reviewed
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Moustaki, Irini; Joreskog, Karl G.; Mavridis, Dimitris – Structural Equation Modeling, 2004
We consider a general type of model for analyzing ordinal variables with covariate effects and 2 approaches for analyzing data for such models, the item response theory (IRT) approach and the PRELIS-LISREL (PLA) approach. We compare these 2 approaches on the basis of 2 examples, 1 involving only covariate effects directly on the ordinal variables…
Descriptors: Item Response Theory, Models, Comparative Analysis, Factor Analysis