T. Asparouhov, B. Muthén (2009)
Exploratory Structural Equation ModelingStructural Equation Modeling: A Multidisciplinary Journal, 16
J. Fox (2010)
Bayesian Item Response Modeling
D. Sörbom (1989)
Model modificationPsychometrika, 54
B. Muthén (2013)
New Methods for the Study of Measurement Invariance with Many Groups
(2013)
BSEM measurement invariance analysis: Mplus Web Note 17
T. Asparouhov (2012)
General Random Effect Latent Variable Modeling : Random Subjects , Items , Contexts , and Parameters
B. Muthén, T. Asparouhov (2012)
Bayesian structural equation modeling: a more flexible representation of substantive theory.Psychological methods, 17 3
(2011)
Statistical approaches to measurement invariance
M. Jong, J. Steenkamp, J. Fox (2007)
Relaxing Measurement Invariance in Cross-National Consumer Research Using a Hierarchical IRT ModelJournal of Consumer Research, 34
B. Muthén, T. Asparouhov (2010)
Bayesian SEM : A more flexible representation of substantive theory
(2010)
Bayesian Analysis Using Mplus
T. Asparouhov, B. Muthén (2010)
Bayesian Analysis Using Mplus: Technical Implementation
C. Beierlein, E. Davidov, P. Schmidt, S. Schwartz, Beatrice Rammstedt (2012)
Testing the discriminant validity of Schwartz’ Portrait Value Questionnaire items – A replication and extension of Knoppen and Saris (2009)Survey research methods, 6
R. Jennrich (2006)
Rotation to Simple Loadings Using Component Loss Functions: The Oblique CasePsychometrika, 71
This article presents a new method for multiple-group confirmatory factor analysis (CFA), referred to as the alignment method. The alignment method can be used to estimate group-specific factor means and variances without requiring exact measurement invariance. A strength of the method is the ability to conveniently estimate models for many groups. The method is a valuable alternative to the currently used multiple-group CFA methods for studying measurement invariance that require multiple manual model adjustments guided by modification indexes. Multiple-group CFA is not practical with many groups due to poor model fit of the scalar model and too many large modification indexes. In contrast, the alignment method is based on the configural model and essentially automates and greatly simplifies measurement invariance analysis. The method also provides a detailed account of parameter invariance for every model parameter in every group.
Structural Equation Modeling: A Multidisciplinary Journal – Taylor & Francis
Published: Oct 2, 2014
Keywords: measurement invariance; Mplus; multiple group factor analysis
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