NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 13 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Keke Lai – Structural Equation Modeling: A Multidisciplinary Journal, 2024
When a researcher proposes an SEM model to explain the dynamics among some latent variables, the real question in model evaluation is the fit of the model's structural part. A composite index that lumps the fit of the structural part and measurement part does not directly address that question. The need for more attention to structural-level fit…
Descriptors: Goodness of Fit, Structural Equation Models, Statistics, Statistical Distributions
Peer reviewed Peer reviewed
Direct linkDirect link
Ismail Cuhadar; Ömür Kaya Kalkan – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Simulation studies are needed to investigate how many score categories are sufficient to treat ordered categorical data as continuous, particularly for bifactor models. The current simulation study aims to address such needs by investigating the performance of estimation methods in the bifactor models with ordered categorical data. Results support…
Descriptors: Predictor Variables, Structural Equation Models, Sample Size, Evaluation Methods
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Haixiang Zhang – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Mediation analysis is an important statistical tool in many research fields, where the joint significance test is widely utilized for examining mediation effects. Nevertheless, the limitation of this mediation testing method stems from its conservative Type I error, which reduces its statistical power and imposes certain constraints on its…
Descriptors: Structural Equation Models, Statistical Significance, Robustness (Statistics), Comparative Testing
Peer reviewed Peer reviewed
Direct linkDirect link
Sarah Depaoli; Sonja D. Winter; Haiyan Liu – Structural Equation Modeling: A Multidisciplinary Journal, 2024
We extended current knowledge by examining the performance of several Bayesian model fit and comparison indices through a simulation study using the confirmatory factor analysis. Our goal was to determine whether commonly implemented Bayesian indices can detect specification errors. Specifically, we wanted to uncover any differences in detecting…
Descriptors: Structural Equation Models, Bayesian Statistics, Comparative Testing, Evaluation Utilization
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Daniel McNeish; Melissa G. Wolf – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Despite the popularity of traditional fit index cutoffs like RMSEA [less than or equal to] 0.06 and CFI [greater than or equal to] 0.95, several studies have noted issues with overgeneralizing traditional cutoffs. Computational methods have been proposed to avoid overgeneralization by deriving cutoffs specifically tailored to the characteristics…
Descriptors: Structural Equation Models, Cutting Scores, Generalizability Theory, Error of Measurement
Peer reviewed Peer reviewed
Direct linkDirect link
Bang Quan Zheng; Peter M. Bentler – Structural Equation Modeling: A Multidisciplinary Journal, 2025
This paper aims to advocate for a balanced approach to model fit evaluation in structural equation modeling (SEM). The ongoing debate surrounding chi-square test statistics and fit indices has been characterized by ambiguity and controversy. Despite the acknowledged limitations of relying solely on the chi-square test, its careful application can…
Descriptors: Monte Carlo Methods, Structural Equation Models, Goodness of Fit, Robustness (Statistics)
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Zachary J. Roman; Patrick Schmidt; Jason M. Miller; Holger Brandt – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Careless and insufficient effort responding (C/IER) is a situation where participants respond to survey instruments without considering the item content. This phenomena adds noise to data leading to erroneous inference. There are multiple approaches to identifying and accounting for C/IER in survey settings, of these approaches the best performing…
Descriptors: Structural Equation Models, Bayesian Statistics, Response Style (Tests), Robustness (Statistics)
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Honggang Liu; Majid Elahi Shirvan; Tahereh Taherian – Studies in Second Language Learning and Teaching, 2025
The current research aimed to examine the relationships among three key aspects of the language learning process, namely, foreign language boredom (FLB), English language engagement (ELE), and academic buoyancy (AB), utilizing data collected from 2,992 Chinese language learners. In order to strengthen the accuracy and robustness of the results, we…
Descriptors: Learner Engagement, English (Second Language), Second Language Learning, Second Language Instruction