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E. Damiano D'Urso; Jesper Tijmstra; Jeroen K. Vermunt; Kim De Roover – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Measurement invariance (MI) is required for validly comparing latent constructs measured by multiple ordinal self-report items. Non-invariances may occur when disregarding (group differences in) an acquiescence response style (ARS; an agreeing tendency regardless of item content). If non-invariance results solely from neglecting ARS, one should…
Descriptors: Error of Measurement, Structural Equation Models, Construct Validity, Measurement Techniques
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
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
Hoi, Vo Ngoc; Le Hang, Ho – Journal of Computer Assisted Learning, 2021
Enhancing student engagement plays a critical role in reducing student drop-out rate in online learning as students usually feel isolated and disconnected in this learning environment. This requires a clear conceptualization of the student engagement construct and its underlying structure. However, the conceptual understanding of the student…
Descriptors: Learner Engagement, Electronic Learning, Structural Equation Models, Factor Analysis
Jin, Ying – International Journal of Behavioral Development, 2020
This research examines the performance of the previously proposed cutoff values of alternative fit indices (i.e., change in comparative fit index [(delta)CFI], change in Tucker-Lewis index [(delta)TLI], and change in root mean squared error of approximation [(delta)RMSEA]) to evaluate measurement invariance for exploratory structural equation…
Descriptors: Structural Equation Models, Goodness of Fit, Measurement, Factor Analysis
Yuanfang Liu; Mark H. C. Lai; Ben Kelcey – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Measurement invariance holds when a latent construct is measured in the same way across different levels of background variables (continuous or categorical) while controlling for the true value of that construct. Using Monte Carlo simulation, this paper compares the multiple indicators, multiple causes (MIMIC) model and MIMIC-interaction to a…
Descriptors: Classification, Accuracy, Error of Measurement, Correlation
Son, Sookyoung; Hong, Sehee – Educational and Psychological Measurement, 2021
The purpose of this two-part study is to evaluate methods for multiple group analysis when the comparison group is at the within level with multilevel data, using a multilevel factor mixture model (ML FMM) and a multilevel multiple-indicators multiple-causes (ML MIMIC) model. The performance of these methods was evaluated integrally by a series of…
Descriptors: Hierarchical Linear Modeling, Factor Analysis, Structural Equation Models, Groups
Gonzales, Joseph E. – Measurement: Interdisciplinary Research and Perspectives, 2021
JMP® Pro has introduced a new structural equation modeling (SEM) platform to its suite of multivariate methods of analysis. Utilizing their graphical user interface, JMP Pro has created a SEM platform that is easily navigable for both experienced and novice SEM users. As a new platform, JMP Pro does not have the capacity to implement certain…
Descriptors: Structural Equation Models, Multivariate Analysis, Usability, Factor Analysis
Alshammari, Sultan Hammad – International Journal of Technology in Education, 2022
This study investigates students' readiness to adopt Massive Open Online Courses (MOOCs) at the University of Ha'il. It applied Student Online Learning Readiness (SOLR) model to examine the constructs that might influence students' readiness toward using MOOCs. A questionnaire was sent to students that measured the model's latent constructs:…
Descriptors: Learning Readiness, Online Courses, Structural Equation Models, College Students
Fu, Yuanshu; Wen, Zhonglin; Wang, Yang – Educational and Psychological Measurement, 2022
Composite reliability, or coefficient omega, can be estimated using structural equation modeling. Composite reliability is usually estimated under the basic independent clusters model of confirmatory factor analysis (ICM-CFA). However, due to the existence of cross-loadings, the model fit of the exploratory structural equation model (ESEM) is…
Descriptors: Comparative Analysis, Structural Equation Models, Factor Analysis, Reliability
Beauducel, André; Hilger, Norbert – Educational and Psychological Measurement, 2022
In the context of Bayesian factor analysis, it is possible to compute plausible values, which might be used as covariates or predictors or to provide individual scores for the Bayesian latent variables. Previous simulation studies ascertained the validity of mean plausible values by the mean squared difference of the mean plausible values and the…
Descriptors: Bayesian Statistics, Factor Analysis, Prediction, Simulation
Haiyan Liu; Sarah Depaoli; Lydia Marvin – Structural Equation Modeling: A Multidisciplinary Journal, 2022
The deviance information criterion (DIC) is widely used to select the parsimonious, well-fitting model. We examined how priors impact model complexity (pD) and the DIC for Bayesian CFA. Study 1 compared the empirical distributions of pD and DIC under multivariate (i.e., inverse Wishart) and separation strategy (SS) priors. The former treats the…
Descriptors: Structural Equation Models, Bayesian Statistics, Goodness of Fit, Factor Analysis
Morley, Alicen; Nissen, Jayson M.; Van Dusen, Ben – Physical Review Physics Education Research, 2023
Instructors and researchers often use research-based assessments to identify the impact of instructional activities. These investigations often focus on issues of diversity, equity, and inclusions by comparing outcomes across social identity groups (e.g., gender, race, and class). Comparisons across groups assume the assessments measure the same…
Descriptors: Error of Measurement, Racial Differences, Gender Differences, Test Validity
Fatih Orcan – International Journal of Assessment Tools in Education, 2023
Among all, Cronbach's Alpha and McDonald's Omega are commonly used for reliability estimations. The alpha uses inter-item correlations while omega is based on a factor analysis result. This study uses simulated ordinal data sets to test whether the alpha and omega produce different estimates. Their performances were compared according to the…
Descriptors: Statistical Analysis, Monte Carlo Methods, Correlation, Factor Analysis
Butakor, Paul K.; Guo, Qi; Adebanji, Atinuke O. – Psychology in the Schools, 2021
The purpose of the study was to examine the causal relationship between teachers' emotional intelligence, job satisfaction, professional identity, and work engagement. And to achieve this purpose, a questionnaire consisting of four scales was administered to 260 teachers selected from the Adentan Municipal in the Greater Accra Region. Exploratory…
Descriptors: Structural Equation Models, Foreign Countries, Emotional Intelligence, Job Satisfaction

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