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Kentaro Hayashi; Ke-Hai Yuan; Peter M. Bentler – Grantee Submission, 2025
Most existing studies on the relationship between factor analysis (FA) and principal component analysis (PCA) focus on approximating the common factors by the first few components via the closeness between their loadings. Based on a setup in Bentler and de Leeuw (Psychometrika 76:461-470, 2011), this study examines the relationship between FA…
Descriptors: Factor Analysis, Comparative Analysis, Correlation, Evaluation Criteria
Zhixin Wang – ProQuest LLC, 2024
In this work, we delve into geometric analysis, particularly examining the interplay between lower bounds on Ricci curvature and specific functionals. Our exploration begins with an investigation into the implications of Yamabe invariants for asymptotically Poincare-Einstein manifolds and their conformal boundaries under conditions of…
Descriptors: Geometric Concepts, Mathematics, Geometry, Correlation
Ke-Hai Yuan; Zhiyong Zhang – Grantee Submission, 2025
Most methods for structural equation modeling (SEM) focused on the analysis of covariance matrices. However, "Historically, interesting psychological theories have been phrased in terms of correlation coefficients." This might be because data in social and behavioral sciences typically do not have predefined metrics. While proper methods…
Descriptors: Correlation, Statistical Analysis, Models, Tests
Yan Xia; Xinchang Zhou – Educational and Psychological Measurement, 2025
Parallel analysis has been considered one of the most accurate methods for determining the number of factors in factor analysis. One major advantage of parallel analysis over traditional factor retention methods (e.g., Kaiser's rule) is that it addresses the sampling variability of eigenvalues obtained from the identity matrix, representing the…
Descriptors: Factor Analysis, Statistical Analysis, Evaluation Methods, Sampling
Tyler M. Moore; Katherine C. Lopez; J. Cobb Scott; Jack C. Lennon; Akira Di Sandro; Eirini Zoupou; Alesandra Gorgone; Monica E. Calkins; Daniel H. Wolf; Joseph W. Kable; Kosha Ruparel; Raquel E. Gur; Ruben C. Gur – Journal of Psychoeducational Assessment, 2025
The Penn Computerized Neurocognitive Battery (CNB) is a collection of tests validated using neuroimaging, genetics, and other criteria. An updated version of the CNB was constructed in which all tests were converted to either computerized adaptive (CAT) or abbreviated forms. In a mixed community/clinical sample (N = 307; mean age = 25.9 years;…
Descriptors: Computer Assisted Testing, Cognitive Ability, Genetics, Adaptive Testing
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
Tenko Raykov; Lisa Calvocoressi; Randall E. Schumacker – Measurement: Interdisciplinary Research and Perspectives, 2024
This paper is concerned with the process of selecting between the increasingly popular bi-factor model and the second-order factor model in measurement research. It is indicated that in certain settings widely used in empirical studies, the second-order model is nested in the bi-factor model and obtained from the latter after imposing appropriate…
Descriptors: Factor Analysis, Decision Making, Computer Software, Measurement Techniques
Jingwen Wang; Xiaohong Yang; Dujuan Liu – International Journal of Web-Based Learning and Teaching Technologies, 2024
The large scale expansion of online courses has led to the crisis of course quality issues. In this study, we first established an evaluation index system for online courses using factor analysis, encompassing three key constructs: course resource construction, course implementation, and teaching effectiveness. Subsequently, we employed factor…
Descriptors: Educational Quality, Online Courses, Course Evaluation, Models
Karl Schweizer; Andreas Gold; Dorothea Krampen; Stefan Troche – Educational and Psychological Measurement, 2024
Conceptualizing two-variable disturbances preventing good model fit in confirmatory factor analysis as item-level method effects instead of correlated residuals avoids violating the principle that residual variation is unique for each item. The possibility of representing such a disturbance by a method factor of a bifactor measurement model was…
Descriptors: Correlation, Factor Analysis, Measurement Techniques, Item Analysis
André Beauducel; Norbert Hilger; Tobias Kuhl – Educational and Psychological Measurement, 2024
Regression factor score predictors have the maximum factor score determinacy, that is, the maximum correlation with the corresponding factor, but they do not have the same inter-correlations as the factors. As it might be useful to compute factor score predictors that have the same inter-correlations as the factors, correlation-preserving factor…
Descriptors: Scores, Factor Analysis, Correlation, Predictor Variables
Pere J. Ferrando; Ana Hernández-Dorado; Urbano Lorenzo-Seva – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A frequent criticism of exploratory factor analysis (EFA) is that it does not allow correlated residuals to be modelled, while they can be routinely specified in the confirmatory (CFA) model. In this article, we propose an EFA approach in which both the common factor solution and the residual matrix are unrestricted (i.e., the correlated residuals…
Descriptors: Correlation, Factor Analysis, Models, Goodness of Fit
Ehri Ryu – Society for Research on Educational Effectiveness, 2024
Background/Context: Confirmatory factor analysis (CFA) model is a commonly adopted framework to estimate and test a measurement model. Once a well-fitting final CFA model is selected, the selected model may be used to test structural relationships of the latent constructs with other variables, to construct a test with desired reliability and…
Descriptors: Research Problems, Factor Analysis, Scores, Computation
Hoang V. Nguyen; Niels G. Waller – Educational and Psychological Measurement, 2024
We conducted an extensive Monte Carlo study of factor-rotation local solutions (LS) in multidimensional, two-parameter logistic (M2PL) item response models. In this study, we simulated more than 19,200 data sets that were drawn from 96 model conditions and performed more than 7.6 million rotations to examine the influence of (a) slope parameter…
Descriptors: Monte Carlo Methods, Item Response Theory, Correlation, Error of Measurement
Cátia Marques; Íris M. Oliveira; Jaisso Vautero; Ana Daniela Silva – International Journal for Educational and Vocational Guidance, 2024
This study examined the psychometric properties of the Career Adapt-Abilities Scale in a Lebanese sample. The study includes 236 Lebanese citizens (54.2% women; M[subscript age] = 30.14). Confirmatory factor analyses indicated that a hierarchical model yielded a good fit, with the CAAS measuring four distinct dimensions that can be combined in a…
Descriptors: Psychometrics, Career Development, Factor Analysis, Goodness of Fit
Riyad Salim Al-Issa; Steven Krauss; Samsilah Roslan; Haslinda Abdullah – Journal of Beliefs & Values, 2025
Previous studies have linked religiosity to a variety of positive outcomes for young people. However, further investigation into the underlying mechanisms that drive this connection is necessary to facilitate these positive outcomes. Some studies have suggested that afterlife reward and punishment beliefs play a role in this connection, as they…
Descriptors: Foreign Countries, Factor Analysis, Correlation, Beliefs