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E. Damiano D'Urso; Jesper Tijmstra; Jeroen K. Vermunt; Kim De Roover – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Measurement invariance (MI) is required for validly comparing latent constructs measured by multiple ordinal self-report items. Non-invariances may occur when disregarding (group differences in) an acquiescence response style (ARS; an agreeing tendency regardless of item content). If non-invariance results solely from neglecting ARS, one should…
Descriptors: Error of Measurement, Structural Equation Models, Construct Validity, Measurement Techniques
Jones-Farmer, L. Allison – Structural Equation Modeling: A Multidisciplinary Journal, 2010
When comparing latent variables among groups, it is important to first establish the equivalence or invariance of the measurement model across groups. Confirmatory factor analysis (CFA) is a commonly used methodological approach to examine measurement equivalence/invariance (ME/I). Within the CFA framework, the chi-square goodness-of-fit test and…
Descriptors: Factor Structure, Factor Analysis, Evaluation Research, Goodness of Fit
Fan, Xitao; Sivo, Stephen A. – Structural Equation Modeling: A Multidisciplinary Journal, 2009
In research concerning model invariance across populations, researchers have discussed the limitations of the conventional chi-square difference test ([Delta] chi-square test). There have been some research efforts in using goodness-of-fit indexes (i.e., [Delta]goodness-of-fit indexes) for assessing multisample model invariance, and some specific…
Descriptors: Monte Carlo Methods, Goodness of Fit, Statistical Analysis, Simulation
Jones-Farmer, L. Allison; Pitts, Jennifer P.; Rainer, R. Kelly – Structural Equation Modeling: A Multidisciplinary Journal, 2008
Although SAS PROC CALIS is not designed to perform multigroup comparisons, it is believed that SAS can be "tricked" into doing so for groups of equal size. At present, there are no comprehensive examples of the steps involved in performing a multigroup comparison in SAS. The purpose of this article is to illustrate these steps. We demonstrate…
Descriptors: Goodness of Fit, Structural Equation Models, Measurement Techniques, Interpersonal Communication
Asparouhov, Tihomir; Muthen, Bengt – Structural Equation Modeling: A Multidisciplinary Journal, 2009
Exploratory factor analysis (EFA) is a frequently used multivariate analysis technique in statistics. Jennrich and Sampson (1966) solved a significant EFA factor loading matrix rotation problem by deriving the direct Quartimin rotation. Jennrich was also the first to develop standard errors for rotated solutions, although these have still not made…
Descriptors: Structural Equation Models, Testing, Factor Analysis, Research Methodology
Kim, Sooyeon; Hagtvet, Knut A. – Structural Equation Modeling: A Multidisciplinary Journal, 2003
This study focused on misspecifications in composing parcels to represent a latent construct. Two measurement design factors, item reliability and intercorrelations among parcels, defined 12 true unidimensional parcel models. Deviations from the true model were examined via a 2-facet measurement model in which items and parcels represented the 2…
Descriptors: Simulation, Factor Structure, Measurement Techniques, Goodness of Fit