NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 3 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Timothy R. Konold; Elizabeth A. Sanders; Kelvin Afolabi – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Measurement invariance (MI) is an essential part of validity evidence concerned with ensuring that tests function similarly across groups, contexts, and time. Most evaluations of MI involve multigroup confirmatory factor analyses (MGCFA) that assume simple structure. However, recent research has shown that constraining non-target indicators to…
Descriptors: Evaluation Methods, Error of Measurement, Validity, Monte Carlo Methods
Peer reviewed Peer reviewed
Direct linkDirect link
Bang Quan Zheng; Peter M. Bentler – Structural Equation Modeling: A Multidisciplinary Journal, 2025
This paper aims to advocate for a balanced approach to model fit evaluation in structural equation modeling (SEM). The ongoing debate surrounding chi-square test statistics and fit indices has been characterized by ambiguity and controversy. Despite the acknowledged limitations of relying solely on the chi-square test, its careful application can…
Descriptors: Monte Carlo Methods, Structural Equation Models, Goodness of Fit, Robustness (Statistics)
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Fatih Orçan – International Journal of Assessment Tools in Education, 2025
Factor analysis is a statistical method to explore the relationships among observed variables and identify latent structures. It is crucial in scale development and validity analysis. Key factors affecting the accuracy of factor analysis results include the type of data, sample size, and the number of response categories. While some studies…
Descriptors: Factor Analysis, Factor Structure, Item Response Theory, Sample Size