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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
Chunhua Cao; Yan Wang; Eunsook Kim – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Multilevel factor mixture modeling (FMM) is a hybrid of multilevel confirmatory factor analysis (CFA) and multilevel latent class analysis (LCA). It allows researchers to examine population heterogeneity at the within level, between level, or both levels. This tutorial focuses on explicating the model specification of multilevel FMM that considers…
Descriptors: Hierarchical Linear Modeling, Factor Analysis, Nonparametric Statistics, Statistical Analysis
Tugay Kaçak; Abdullah Faruk Kiliç – International Journal of Assessment Tools in Education, 2025
Researchers continue to choose PCA in scale development and adaptation studies because it is the default setting and overestimates measurement quality. When PCA is utilized in investigations, the explained variance and factor loadings can be exaggerated. PCA, in contrast to the models given in the literature, should be investigated in…
Descriptors: Factor Analysis, Monte Carlo Methods, Mathematical Models, Sample Size
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
A. R. Georgeson – Structural Equation Modeling: A Multidisciplinary Journal, 2025
There is increasing interest in using factor scores in structural equation models and there have been numerous methodological papers on the topic. Nevertheless, sum scores, which are computed from adding up item responses, continue to be ubiquitous in practice. It is therefore important to compare simulation results involving factor scores to…
Descriptors: Structural Equation Models, Scores, Factor Analysis, Statistical Bias
Mussa Saidi Abubakari; Gamal Abdul Nasir Zakaria; Juraidah Musa – Discover Education, 2025
In the contemporary world of digitalisation, comprehensive digital competence (DC) is and should be an integral part of students' repertoire to guarantee not only academic but also professional success. However, the level and requirements for DC may vary within specific educational contexts, especially in culturally oriented institutions. This…
Descriptors: College Students, Digital Literacy, Student Evaluation, Foreign Countries
Njål Foldnes; Jonas Moss; Steffen Grønneberg – Structural Equation Modeling: A Multidisciplinary Journal, 2025
We propose new ways of robustifying goodness-of-fit tests for structural equation modeling under non-normality. These test statistics have limit distributions characterized by eigenvalues whose estimates are highly unstable and biased in known directions. To take this into account, we design model-based trend predictions to approximate the…
Descriptors: Goodness of Fit, Structural Equation Models, Robustness (Statistics), Prediction
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
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
Aitana González-Ortiz de Zárate; Helena Roig-Ester; Paulina E. Robalino Guerra; Anja Garone; Carla Quesada-Pallarès – International Journal of Training and Development, 2025
Transfer beliefs are understudied in the training transfer field, whereas structural equation modelling (SEM) has been a widely used technique to study transfer models. New methodologies are needed to study training transfer and network analysis (NA) has emerged as a new approach that provides a visual representation of a given network. We…
Descriptors: Trainees, Student Attitudes, Beliefs, Transfer of Training
Ilkka Ratinen; Jubeen Sharbaf Kashani; Lassi Linnanen – Environmental Education Research, 2025
Current environmental risks, such as climate change and nature loss, force us to look for solutions in every sector of society. A successful sustainability transition requires the manipulation of deep systemic leverage points. Hence, a deep leverage point framework based on sustainability competencies is needed to conceptualise sustainability…
Descriptors: Sustainability, Competency Based Education, Climate, Natural Resources
Dandan Tang; Steven M. Boker; Xin Tong – Structural Equation Modeling: A Multidisciplinary Journal, 2025
The replication crisis in social and behavioral sciences has raised concerns about the reliability and validity of empirical studies. While research in the literature has explored contributing factors to this crisis, the issues related to analytical tools have received less attention. This study focuses on a widely used analytical tool -…
Descriptors: Test Validity, Factor Analysis, Replication (Evaluation), Social Science Research
Manuel T. Rein; Jeroen K. Vermunt; Kim De Roover; Leonie V. D. E. Vogelsmeier – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Researchers often study dynamic processes of latent variables in everyday life, such as the interplay of positive and negative affect over time. An intuitive approach is to first estimate the measurement model of the latent variables, then compute factor scores, and finally use these factor scores as observed scores in vector autoregressive…
Descriptors: Measurement Techniques, Factor Analysis, Scores, Validity
Sara Sadat Hosseini; Hassan Soleimani; Fatemeh Hemmati; Jafar Afshinfar – Iranian Journal of Language Teaching Research, 2025
From the complex dynamic systems theory perspective, evaluating CALL pedagogy involves miscellaneous variables. It seems the ecosystem of the CALL environment necessitates an array of extralinguistic (Ecolinguistically situated) issues to be considered in any appraisal of the CALL milieu. To this end, this paper aims to develop and validate a…
Descriptors: Computer Assisted Instruction, Second Language Instruction, Second Language Learning, Factor Analysis
Ke Hu; Asmaa AlSaqqaf – Australian Journal of Applied Linguistics, 2025
Over the past decade, there has been an increasing emphasis on English for Specific Purposes (ESP) within China's higher education language programs. However, the shift towards ESP presents a multifaceted challenge, particularly for business English teaching at higher education, where speaking proficiency is crucial yet often falls below…
Descriptors: Factor Analysis, Business English, English for Special Purposes, Second Language Learning