Publication Date
In 2025 | 1 |
Since 2024 | 8 |
Since 2021 (last 5 years) | 36 |
Since 2016 (last 10 years) | 132 |
Since 2006 (last 20 years) | 363 |
Descriptor
Source
Author
Marsh, Herbert W. | 5 |
Martin, Andrew J. | 5 |
Davies, Patrick T. | 3 |
Gorges, Julia | 3 |
Hong, Jon-Chao | 3 |
Jones, Brett D. | 3 |
Morin, Alexandre J. S. | 3 |
Nurmi, Jari-Erik | 3 |
Arpaci, Ibrahim | 2 |
Aunola, Kaisa | 2 |
Bagoien, Tor Egil | 2 |
More ▼ |
Publication Type
Journal Articles | 371 |
Reports - Research | 330 |
Reports - Evaluative | 39 |
Tests/Questionnaires | 10 |
Reports - Descriptive | 2 |
Opinion Papers | 1 |
Education Level
Audience
Teachers | 1 |
Location
Turkey | 17 |
Germany | 14 |
China | 11 |
Hong Kong | 10 |
Netherlands | 10 |
Australia | 8 |
South Korea | 7 |
United Kingdom | 6 |
Israel | 5 |
Spain | 5 |
Canada | 4 |
More ▼ |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
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
Jie Fang; Zhonglin Wen; Kit-Tai Hau – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Currently, dynamic structural equation modeling (DSEM) and residual DSEM (RDSEM) are commonly used in testing intensive longitudinal data (ILD). Researchers are interested in ILD mediation models, but their analyses are challenging. The present paper mathematically derived, empirically compared, and step-by-step demonstrated three types (i.e.,…
Descriptors: Structural Equation Models, Mediation Theory, Data Analysis, Longitudinal Studies
Gyeongcheol Cho; Heungsun Hwang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Generalized structured component analysis (GSCA) is a multivariate method for specifying and examining interrelationships between observed variables and components. Despite its data-analytic flexibility honed over the decade, GSCA always defines every component as a linear function of observed variables, which can be less optimal when observed…
Descriptors: Prediction, Methods, Networks, Simulation
Knowlden, Adam P.; Naher, Shabnam – American Journal of Health Education, 2023
Background: Poor sleep is commonplace among traditional entry university students. Lifestyle modifications, such as time management behaviors, may improve sleep quality by allocating sufficient time for sleep and mitigating stress-associated sleep latency inefficiencies. Purpose: The purpose of our study was to evaluate time management behaviors…
Descriptors: Time Management, Student Behavior, Structural Equation Models, Prediction
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
Ke-Hai Yuan; Yongfei Fang – Grantee Submission, 2023
Observational data typically contain measurement errors. Covariance-based structural equation modelling (CB-SEM) is capable of modelling measurement errors and yields consistent parameter estimates. In contrast, methods of regression analysis using weighted composites as well as a partial least squares approach to SEM facilitate the prediction and…
Descriptors: Structural Equation Models, Regression (Statistics), Weighted Scores, Comparative Analysis
Yangqiuting Li; Chandralekha Singh – Physical Review Physics Education Research, 2024
Structural equation modeling (SEM) is a statistical method widely used in educational research to investigate relationships between variables. SEM models are typically constructed based on theoretical foundations and assessed through fit indices. However, a well-fitting SEM model alone is not sufficient to verify the causal inferences underlying…
Descriptors: Structural Equation Models, Statistical Analysis, Educational Research, Causal Models
Hilley, Chanler D.; O'Rourke, Holly P. – International Journal of Behavioral Development, 2022
Researchers in behavioral sciences are often interested in longitudinal behavior change outcomes and the mechanisms that influence changes in these outcomes over time. The statistical models that are typically implemented to address these research questions do not allow for investigation of mechanisms of dynamic change over time. However, latent…
Descriptors: Behavioral Science Research, Research Methodology, Longitudinal Studies, Behavior Change
Miyazaki, Yasuo; Kamata, Akihito; Uekawa, Kazuaki; Sun, Yizhi – Educational and Psychological Measurement, 2022
This paper investigated consequences of measurement error in the pretest on the estimate of the treatment effect in a pretest-posttest design with the analysis of covariance (ANCOVA) model, focusing on both the direction and magnitude of its bias. Some prior studies have examined the magnitude of the bias due to measurement error and suggested…
Descriptors: Error of Measurement, Pretesting, Pretests Posttests, Statistical Bias
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
Yamashita, Takashi; Smith, Thomas J.; Cummins, Phyllis A. – Journal of Educational and Behavioral Statistics, 2021
In order to promote the use of increasingly available large-scale assessment data in education and expand the scope of analytic capabilities among applied researchers, this study provides step-by-step guidance, and practical examples of syntax and data analysis using Maples. Concise overview and key unique aspects of large-scale assessment data…
Descriptors: Learning Analytics, Computer Software, Syntax, Adults
Weiss, Selina; Steger, Diana; Schroeders, Ulrich; Wilhelm, Oliver – Journal of Intelligence, 2020
Intelligence has been declared as a necessary but not sufficient condition for creativity, which was subsequently (erroneously) translated into the so-called threshold hypothesis. This hypothesis predicts a change in the correlation between creativity and intelligence at around 1.33 standard deviations above the population mean. A closer…
Descriptors: Intelligence, Creativity, Prediction, Correlation
John Grinstead; Ramón Padilla-Reyes; Melissa Nieves-Rivera; Morgan Oates – Language Acquisition: A Journal of Developmental Linguistics, 2024
We test children's distributive and collective sentence interpretations and the variables that predict them. In our first experiment, we establish that adult English collective sentences with "the" or "some" in the subject are categorically collective in their interpretations. We further demonstrate that children's collective…
Descriptors: Child Language, Goodness of Fit, Sentences, Prediction
Chi-Jung Sui; Miao-Hsuan Yen; Chun-Yen Chang – Education and Information Technologies, 2024
This study examined the effects of a technology-enhanced intervention on the self-regulation of 262 eighth-grade students, employing information and communication technology (ICT) and web-based self-assessment tools set against science learning. The data were analyzed using Bayesian structural equation modeling to unravel the intricate…
Descriptors: Technology Uses in Education, Independent Study, Middle School Students, Grade 8
Sun, Wei; Hong, Jon-Chao; Dong, Yan; Huang, Yue; Fu, Qian – Asia-Pacific Education Researcher, 2023
Online education has made it possible to implement the "classes suspended but learning continues" policy during the COVID-19 outbreak. However, the intangible sense of the online educational setting requires self-directed learning (SDL) and may force students to know the goals of learning that may impact their engagement. To understand…
Descriptors: Independent Study, Online Courses, COVID-19, Pandemics