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Bilge Bal-Sezerel; Deniz Arslan; Ugur Sak – Measurement: Interdisciplinary Research and Perspectives, 2025
In this study, the factorial invariance of the ASIS (Anadolu-Sak Intelligence Scale) was examined across time. Data were obtained from there groups of first-grade students who were administered the ASIS in 2020, 2021, and 2022. The analyses were conducted using multisample confirmatory factor analyses. Factorial invariance was tested with six…
Descriptors: Intelligence Tests, Grade 1, Factor Structure, Scores
Bodo Przibilla; Chiara Enderle; Gino Casale; David Scheer; Anett Platte; Conny Melzer; Tatjana Leidig – European Journal of Education, 2025
Based on previous research, it can be assumed that teachers' self-efficacy (TSE) varies across situations, domains and individual students' behaviors confronting teachers with particularly challenging tasks. The construct of student-specific TSE is considered informative theoretical basis for understanding the relationship between…
Descriptors: Psychometrics, German, Foreign Countries, Teacher Effectiveness
Adrian Quintero; Emmanuel Lesaffre; Geert Verbeke – Journal of Educational and Behavioral Statistics, 2024
Bayesian methods to infer model dimensionality in factor analysis generally assume a lower triangular structure for the factor loadings matrix. Consequently, the ordering of the outcomes influences the results. Therefore, we propose a method to infer model dimensionality without imposing any prior restriction on the loadings matrix. Our approach…
Descriptors: Bayesian Statistics, Factor Analysis, Factor Structure, Sampling
Timothy R. Konold; Elizabeth A. Sanders – Measurement: Interdisciplinary Research and Perspectives, 2024
Compared to traditional confirmatory factor analysis (CFA), exploratory structural equation modeling (ESEM) has been shown to result in less structural parameter bias when cross-loadings (CLs) are present. However, when model fit is reasonable for CFA (over ESEM), CFA should be preferred on the basis of parsimony. Using simulations, the current…
Descriptors: Structural Equation Models, Factor Analysis, Factor Structure, Goodness of Fit
Naoto Yamashita – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Matrix decomposition structural equation modeling (MDSEM) is introduced as a novel approach in structural equation modeling, contrasting with traditional structural equation modeling (SEM). MDSEM approximates the data matrix using a model generated by the hypothetical model and addresses limitations faced by conventional SEM procedures by…
Descriptors: Structural Equation Models, Factor Structure, Robustness (Statistics), Matrices
Sara Dhaene; Yves Rosseel – Structural Equation Modeling: A Multidisciplinary Journal, 2024
In confirmatory factor analysis (CFA), model parameters are usually estimated by iteratively minimizing the Maximum Likelihood (ML) fit function. In optimal circumstances, the ML estimator yields the desirable statistical properties of asymptotic unbiasedness, efficiency, normality, and consistency. In practice, however, real-life data tend to be…
Descriptors: Factor Analysis, Factor Structure, Maximum Likelihood Statistics, Computation
Sergio Dominguez-Lara; Mario A. Trógolo; Rodrigo Moreta-Herrera; Diego Vaca-Quintana; Manuel Fernández-Arata; Ana Paredes-Proaño – Journal of Psychoeducational Assessment, 2025
Academic engagement plays a crucial role in students' learning and performance. One of the most popular measures for assessing this construct is the Utrecht Work Engagement Scale for Students (UWES-S), which is based on a tridimensional conceptualization consisting of dedication, vigor, and absorption. However, prior research on its factor…
Descriptors: Learner Engagement, College Students, Foreign Countries, Factor Analysis
Michael D. Wray; Matthew R. Reynolds – Journal of Psychoeducational Assessment, 2025
The KeyMath-3 Diagnostic Assessment (KM-3) is an individually-administered math assessment used in educational placement and diagnostic decisions. It includes 10 subtests making up Basic Concepts, Operations, and Applications indexes and a "Total Test" composite that measures overall math ability. Here, covariances among subtests from…
Descriptors: Diagnostic Tests, Mathematics Tests, Arithmetic, Factor Analysis
Lingbo Tong; Wen Qu; Zhiyong Zhang – Grantee Submission, 2025
Factor analysis is widely utilized to identify latent factors underlying the observed variables. This paper presents a comprehensive comparative study of two widely used methods for determining the optimal number of factors in factor analysis, the K1 rule, and parallel analysis, along with a more recently developed method, the bass-ackward method.…
Descriptors: Factor Analysis, Monte Carlo Methods, Statistical Analysis, Sample Size
Sena Dogruyol; Bilge Bakir Aygar; Nezaket Bilge Uzun; Asena Yucedaglar – Journal on Educational Psychology, 2024
The Satisfaction with Life Scale (SWLS), a popular and widely used measurement tool in cross-cultural research, evaluates life satisfaction. Even though numerous studies have demonstrated factorial validity across a range of samples and cultures, the topic of factorial invariance across various subgroups is still up for debate. There are…
Descriptors: Measures (Individuals), Life Satisfaction, Factor Structure, Models
Chunhua Cao; Xinya Liang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Cross-loadings are common in multiple-factor confirmatory factor analysis (CFA) but often ignored in measurement invariance testing. This study examined the impact of ignoring cross-loadings on the sensitivity of fit measures (CFI, RMSEA, SRMR, SRMRu, AIC, BIC, SaBIC, LRT) to measurement noninvariance. The manipulated design factors included the…
Descriptors: Goodness of Fit, Error of Measurement, Sample Size, Factor Analysis
Yavuz Ercan Gül; Rüstü Yesil – Problems of Education in the 21st Century, 2024
Although equality of opportunity in education is a current and important issue, most of the studies on this subject are based on theoretical studies rather than empirical studies. The main reason for this can be said to be the lack of a valid and reliable measurement tool in this field. For this reason, this study aims to develop a valid and…
Descriptors: Psychometrics, Equal Education, Educational Opportunities, Factor Analysis
Philipp Sterner; Kim De Roover; David Goretzko – Structural Equation Modeling: A Multidisciplinary Journal, 2025
When comparing relations and means of latent variables, it is important to establish measurement invariance (MI). Most methods to assess MI are based on confirmatory factor analysis (CFA). Recently, new methods have been developed based on exploratory factor analysis (EFA); most notably, as extensions of multi-group EFA, researchers introduced…
Descriptors: Error of Measurement, Measurement Techniques, Factor Analysis, Structural Equation Models
Sacide Güzin Mazman Akar – Journal of Education and Learning (EduLearn), 2025
Disengagement is considered a significant component that affects the success, participation, and activity of the students in the online course. Reviewing the literature revealed the lack of a measurement tool for assessing students' disengagement in online courses. This study aimed to develop a scale that examines student disengagement in online…
Descriptors: Learner Engagement, Online Courses, Undergraduate Students, Measures (Individuals)
Maria Meinerding; Jeremiah Weinstock; Jillon Vander Wal; Terri L. Weaver – Journal of American College Health, 2024
Objectives: Food and Alcohol Disturbance (FAD) is the phenomenon in which individuals exhibit co-occurring hazardous alcohol and eating behaviors to either negate caloric intake associated with alcohol and/or maximize intoxication. While the Compensatory Eating and Behaviors in Response to Alcohol Scale (CEBRACS) is the most widely used measure to…
Descriptors: Drinking, Alcohol Abuse, Eating Disorders, Factor Structure