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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
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
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
Shaila Sharmin; Minh-Hao D. Tran; Weihua Fan; Consuelo Arbona; Allison Master; Yali Zou – Journal of Psychoeducational Assessment, 2025
The study examined the psychometric structure of Basic Needs Satisfaction in General Scale (BNSG-S) with a sample of 495 college students. It compared the original 21-item version (Gagné, 2003) with the shortened 16-item version (Johnston & Finney, 2010), both with and without method effects. A series of confirmatory factor analyses (CFA)…
Descriptors: Need Gratification, Measures (Individuals), Psychometrics, College Faculty
Xijuan Zhang; Hao Wu – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A full structural equation model (SEM) typically consists of both a measurement model (describing relationships between latent variables and observed scale items) and a structural model (describing relationships among latent variables). However, often researchers are primarily interested in testing hypotheses related to the structural model while…
Descriptors: Structural Equation Models, Goodness of Fit, Robustness (Statistics), Factor Structure
Franco-Martínez, Alicia; Alvarado, Jesús M.; Sorrel, Miguel A. – Educational and Psychological Measurement, 2023
A sample suffers range restriction (RR) when its variance is reduced comparing with its population variance and, in turn, it fails representing such population. If the RR occurs over the latent factor, not directly over the observed variable, the researcher deals with an indirect RR, common when using convenience samples. This work explores how…
Descriptors: Factor Analysis, Factor Structure, Scores, Sampling
Cassandra Barber; Cees van der Vleuten; Saad Chahine – Advances in Health Sciences Education, 2024
There is an expectation that health professions schools respond to priority societal health needs. This expectation is largely based on the underlying assumption that schools are aware of the priority needs in their communities. This paper demonstrates how open-access, pan-national health data can be used to create a reliable health index to…
Descriptors: Medical Education, Allied Health Occupations Education, Accountability, Public Health
Hyunjung Lee; Heining Cham – Educational and Psychological Measurement, 2024
Determining the number of factors in exploratory factor analysis (EFA) is crucial because it affects the rest of the analysis and the conclusions of the study. Researchers have developed various methods for deciding the number of factors to retain in EFA, but this remains one of the most difficult decisions in the EFA. The purpose of this study is…
Descriptors: Factor Structure, Factor Analysis, Monte Carlo Methods, Goodness of Fit
Young-Jin Lim – SAGE Open, 2023
The goal of this study was to examine the factorial structure, internal consistency, test-retest reliability, criterion validity, convergent validity, and discriminant validity of the Brief Strengths Scale-12 (BSS-12) in Korean population. The Korean sample comprised 288 college students (68.1% were female), ranging in age 19 to 30 years (mean age…
Descriptors: Foreign Countries, Factor Structure, Test Reliability, Test Validity
Mohammad Mehdi Latifi; Dariush Tahmasebi Aghbelaghi; Sajad Khani Pordanjani – European Journal of Education, 2025
The present study sought to assess the psychometric properties of the Iranian adaptation of the Vietnam Teacher Resilience Scale for Asia (VITRS), referred to as the Iranian Teachers' Resilience Scale (ITRS) and to examine its measurement invariance across middle and high school teachers in Iran. In total, 700 participants completed the…
Descriptors: Resilience (Psychology), Error of Measurement, Factor Analysis, Teacher Attitudes
Elizabeth B. Vaughan; A. Montoya-Cowan; Jack Barbera – Chemistry Education Research and Practice, 2024
The Meaningful Learning in the Laboratory Instrument (MLLI) was designed to measure students' expectations before and after their laboratory courses and experiences. Although the MLLI has been used in various studies and laboratory environments to investigate students' cognitive and affective laboratory expectations, the authors of the instrument…
Descriptors: Test Validity, Test Reliability, Expectation, Measures (Individuals)
Christophe Dierendonck – International Education Studies, 2024
This study is aimed at validating the French version of the Effort-Reward Imbalance Questionnaire for Teachers. The instrument was pretested before being administered in a large-scale study with elementary school teachers. Dimensionality of the instrument was examined using the bifactor exploratory structural equation modeling (ESEM) framework.…
Descriptors: Teacher Surveys, Questionnaires, Teacher Persistence, Rewards
Cristian Zanon; Nan Zhao; Nursel Topkaya; Ertugrul Sahin; David L. Vogel; Melissa M. Ertl; Samineh Sanatkar; Hsin-Ya Liao; Mark Rubin; Makilim N. Baptista; Winnie W. S. Mak; Fatima Rashed Al-Darmaki; Georg Schomerus; Ying-Fen Wang; Dalia Nasvytiene – International Journal of Testing, 2025
Examinations of the internal structure of the Depression, Anxiety, and Stress Scale-21 (DASS-21) have yielded inconsistent conclusions within and across cultural contexts. This study examined the dimensionality and reliability of the DASS-21 across three theoretically plausible factor structures (i.e., unidimensional, oblique three-factor, and…
Descriptors: Anxiety, Depression (Psychology), Psychometrics, Cultural Context
Yanjing Cao; Chenchen Xu; Shan Lu; Qi Li; Jing Xiao – Psychology in the Schools, 2025
The patient health questionnaire-9 (PHQ-9) is widely utilized in assessing individuals' depression levels. Nevertheless, research regarding its factor structure and measurement invariance remains inadequate. The aim of this study was to delve into the factor structure of the PHQ-9 and to further investigate its measurement invariance across gender…
Descriptors: Factor Structure, Error of Measurement, Factor Analysis, Age Differences