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Kjorte Harra; David Kaplan – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The present work focuses on the performance of two types of shrinkage priors--the horseshoe prior and the recently developed regularized horseshoe prior--in the context of inducing sparsity in path analysis and growth curve models. Prior research has shown that these horseshoe priors induce sparsity by at least as much as the "gold…
Descriptors: Structural Equation Models, Bayesian Statistics, Regression (Statistics), Statistical Inference
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Ke-Hai Yuan; Zhiyong Zhang; Lijuan Wang – Grantee Submission, 2024
Mediation analysis plays an important role in understanding causal processes in social and behavioral sciences. While path analysis with composite scores was criticized to yield biased parameter estimates when variables contain measurement errors, recent literature has pointed out that the population values of parameters of latent-variable models…
Descriptors: Structural Equation Models, Path Analysis, Weighted Scores, Comparative Testing
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Sim, Mikyung; Kim, Su-Young; Suh, Youngsuk – Educational and Psychological Measurement, 2022
Mediation models have been widely used in many disciplines to better understand the underlying processes between independent and dependent variables. Despite their popularity and importance, the appropriate sample sizes for estimating those models are not well known. Although several approaches (such as Monte Carlo methods) exist, applied…
Descriptors: Sample Size, Statistical Analysis, Predictor Variables, Path Analysis
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Jak, Suzanne; Li, Hongli; Kolbe, Laura; Jonge, Hannelies; Cheung, Mike W.-L. – Research Synthesis Methods, 2021
Meta-analytic structural equation modeling (MASEM) refers to fitting structural equation models (SEMs) (such as path models or factor models) to meta-analytic data. Currently, fitting MASEMs may be challenging for researchers that are not accustomed to working with R software and packages. Therefore, we developed webMASEM; a web application for…
Descriptors: Meta Analysis, Structural Equation Models, Tutorial Programs, Computer Oriented Programs
Yujiao Mai; Ziqian Xu; Zhiyong Zhang; Ke-Hai Yuan – Grantee Submission, 2023
Structural equation modeling (SEM) is widely used in behavioral, social, and education research. Drawing publication-ready path diagrams for SEM is not a pleasant task with the existing software. The article introduces an open-source web-based graphical application, "semdiag," for drawing WYSIWYG SEM path diagrams interactively. The…
Descriptors: Open Source Technology, Web 2.0 Technologies, Freehand Drawing, Path Analysis
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Osman, Esam; Hardaker, Glenn; Glenn, Liyana Eliza – International Journal of Information and Learning Technology, 2022
Purpose: Overall quantitative research aims to observe certain fundamental principles of logic and scientific frame of reasoning. There continues to be challenges on how quantitative research is conducted in the field of information systems. Design/methodology/approach: Structured equation modelling (SEM) research identifies concerns about the…
Descriptors: Structural Equation Models, Management Information Systems, Misconceptions, Scientific Methodology
Ke-Hai Yuan; Yong Wen; Jiashan Tang – Grantee Submission, 2022
Structural equation modeling (SEM) and path analysis using composite-scores are distinct classes of methods for modeling the relationship of theoretical constructs. The two classes of methods are integrated in the partial-least-squares approach to structural equation modeling (PLS-SEM), which systematically generates weighted composites and uses…
Descriptors: Statistical Analysis, Weighted Scores, Least Squares Statistics, Structural Equation Models
Deng, Lifang; Yuan, Ke-Hai – Grantee Submission, 2022
Structural equation modeling (SEM) has been deemed as a proper method when variables contain measurement errors. In contrast, path analysis with composite-scores is preferred for prediction and diagnosis of individuals. While path analysis with composite-scores has been criticized for yielding biased parameter estimates, recent literature pointed…
Descriptors: Structural Equation Models, Path Analysis, Weighted Scores, Error of Measurement
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Carannante, Maria; Davino, Cristina; Vistocco, Domenico – Studies in Higher Education, 2021
Massive Open Online Courses, universally labelled as MOOCs, become more and more relevant in the era of digitalization of higher education. The availability of free education resources without access restrictions for a plenty of potential users has changed the learning market in a way unthinkable only few decades ago. This form of web-based…
Descriptors: Online Courses, Structural Equation Models, Least Squares Statistics, Measurement
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Ahrari, Seyedali; Roslan, Samsilah; Zaremohzzabieh, Zeinab; Mohd Rasdi, Roziah; Abu Samah, Asnarulkhadi – Cogent Education, 2021
This research aims to analyze studies that have investigated the effects of teacher empowerment on job satisfaction. From the results obtained from the meta-analytic structural equation modeling of 11 studies (N = 19,462), it has been found that the teacher empowerment model and job satisfaction are meaningfully correlated. The findings have also…
Descriptors: Teacher Empowerment, Job Satisfaction, Meta Analysis, Path Analysis
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Hsiao, Yu-Yu; Kwok, Oi-Man; Lai, Mark H. C. – Educational and Psychological Measurement, 2018
Path models with observed composites based on multiple items (e.g., mean or sum score of the items) are commonly used to test interaction effects. Under this practice, researchers generally assume that the observed composites are measured without errors. In this study, we reviewed and evaluated two alternative methods within the structural…
Descriptors: Error of Measurement, Testing, Scores, Models
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Ben Kelcey; Fangxing Bai; Amota Ataneka; Yanli Xie; Kyle Cox – Society for Research on Educational Effectiveness, 2024
We develop a structural after measurement (SAM) method for structural equation models (SEMs) that accommodates missing data. The results show that the proposed SAM missing data estimator outperforms conventional full information (FI) estimators in terms of convergence, bias, and root-mean-square-error in small-to-moderate samples or large samples…
Descriptors: Structural Equation Models, Research Problems, Error of Measurement, Maximum Likelihood Statistics
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Malmström, Malin; Öqvist, Anna – International Journal of School & Educational Psychology, 2018
Little empirical evidence is available on what drives young people to engage in higher education. Such knowledge is crucial in order to motivate students to make the most of their potential. This study surveyed a total of 294 Swedish high school students. The result shows that intentions play a mediating role between students' attitudes and the…
Descriptors: Student Attitudes, Intention, Higher Education, Models
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Akar, Hüseyin; Dogan, Yildiz Burcu; Üstüner, Mehmet – European Journal of Contemporary Education, 2018
This research aimed to investigate the relationships between positive and negative perfectionisms, self-handicapping, self-efficacy and academic achievement. For this purpose, an extensive literature review was conducted and a model was suggested. Structural equation model was employed to test the model. The study group of the research consisted…
Descriptors: Self Concept Measures, Self Efficacy, Correlation, Academic Achievement
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Howard, Steven J.; Vasseleu, E.; Neilsen-Hewett, C.; de Rosnay, M.; Williams, K. E. – Child & Youth Care Forum, 2022
Background: Over the past few decades early self-regulation has been identified as foundational to positive learning and wellbeing trajectories. As a consequence, a wide range of approaches have been developed to capture children's developmental progress in self-regulation. Little is known, however, about whether and which of these are reliable…
Descriptors: Prediction, School Readiness, Self Control, Preschool Children
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