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Sideridis, Georgios D.; Jaffari, Fathima – Measurement and Evaluation in Counseling and Development, 2022
The present study describes an R function that implements six corrective procedures developed by Bartlett, Swain, and Yuan in the correction of 21 statistics associated with the omnibus Chi-square test, the residuals, or fit indices in confirmatory factor analysis (CFA) and structural equation modeling (SEM).
Descriptors: Statistical Analysis, Goodness of Fit, Factor Analysis, Structural Equation Models
Lirios, Cruz García – Journal of Interdisciplinary Studies in Education, 2022
The objective of this work was to confirm the factorial structure of collaborative networks in a university in central Mexico during the pandemic. A cross-sectional, psychometric, and confirmatory study was carried out with a sample of 300 administrators, teachers, and students from a public university in central Mexico. From a structural model,…
Descriptors: COVID-19, Pandemics, Public Colleges, Educational Cooperation
Arthur, Yarhands Dissou; Dogbe, Courage Simon Kofi; Asiedu-Addo, Samuel Kwesi – Journal of Applied Research in Higher Education, 2022
Purpose: This study explored the effect of mathematics teaching quality on mathematics achievement among undergraduate students, using the SERVQUAL model. Design/methodology/approach: The sample comprised of 320 first-year undergraduate students of a public university in Ghana. Structural equation modeling (SEM) was run in Amos (v.23) to test the…
Descriptors: Mathematics Achievement, Instructional Effectiveness, Undergraduate Students, Models
Ke-Hai Yuan; Zhiyong Zhang – Grantee Submission, 2022
Structural equation modeling (SEM) is a widely used technique for studies involving latent constructs. While covariance-based SEM (CB-SEM) permits estimating the regression relationship among latent constructs, the parameters governing this relationship do not apply to that among the scored values of the constructs, which are needed for…
Descriptors: Psychometrics, Structural Equation Models, Scores, Least Squares Statistics
Chunhua Cao; Xinya Liang – Structural Equation Modeling: A Multidisciplinary Journal, 2022
Exploratory structural equation modeling (ESEM) allows for the estimation of all cross-loadings, which leads to the number of parameters estimated substantially greater than that in conventional SEM. This study examined the sensitivity of fit measures (CFI, RMSEA, AIC, BIC, SaBIC, LRT) to measurement noninvariance in ESEM. Results suggested that…
Descriptors: Structural Equation Models, Error of Measurement, Computation, Goodness of Fit
van Laar, Saskia; Braeken, Johan – Practical Assessment, Research & Evaluation, 2021
Despite the sensitivity of fit indices to various model and data characteristics in structural equation modeling, these fit indices are used in a rigid binary fashion as a mere rule of thumb threshold value in a search for model adequacy. Here, we address the behavior and interpretation of the popular Comparative Fit Index (CFI) by stressing that…
Descriptors: Goodness of Fit, Structural Equation Models, Sampling, Sample Size
Pósch, Krisztián – Sociological Methods & Research, 2021
Complex social scientific theories are conventionally tested using linear structural equation modeling (SEM). However, the underlying assumptions of linear SEM often prove unrealistic, making the decomposition of direct and indirect effects problematic. Recent advancements in causal mediation analysis can help to address these shortcomings,…
Descriptors: Social Theories, Causal Models, Structural Equation Models, Statistical Analysis
Shih, Ming-Chieh; Tu, Yu-Kang – Research Synthesis Methods, 2021
Network meta-analysis (NMA) compares the efficacy and harm between several treatments by combining direct and indirect evidence. The validity of NMA requires that all available evidence form a coherent network. Failure to meet such requirement is known as inconsistency. The most popular approach to inconsistency detection is to compare the direct…
Descriptors: Networks, Meta Analysis, Evidence, Evaluation Methods
Forthmann, Boris; Szardenings, Carsten; Dumas, Denis – Journal of Creative Behavior, 2021
The equal odds baseline is a parsimonious model that describes the relationship between quantity and quality of output in scientific creativity. Specifically, it is posited that quality is a linear function of quantity, and therefore, strong positive correlations between these two variables are expected. Strong positive correlations also play a…
Descriptors: Creative Thinking, Structural Equation Models, Scientific Research, Correlation
James Ohisei Uanhoro – ProQuest LLC, 2021
This dissertation is a collection of three papers. The first is a conceptual paper, followed by two data analysis papers. All three papers examine the connection between structural equation models and regression models, and how one may better learn, research and apply structural equation models when structural equation models are thought of as…
Descriptors: Structural Equation Models, Bayesian Statistics, Multiple Regression Analysis, Factor Analysis
Lopez, J.; Johnson, C.; Dai, L.; Jones, M. H.; Nodine, M.; Cooper, D.; Eckel, S. – Journal of Psychoeducational Assessment, 2023
The present study examined the convergent validity between two frequently used achievement goal instruments: Patterns of Adaptive Learning Scales (PALS) and the Achievement Goal Questionnaire 3 x 2 (AGQ 3 x 2). Confirmatory factor analysis and structural equation models tested for relationships both within and across the scales in a sample of…
Descriptors: Surveys, Academic Achievement, Goal Orientation, Test Validity
Fayda-Kinik, F. Sehkar – Pegem Journal of Education and Instruction, 2023
In the post-pandemic period, as a result of digitally-surrounded learning environments in higher education institutions (HEIs), some obstacles are observed in learning procedures such as academic procrastination because of poor digital competences. Because of the limited research focusing on specifically digital competences and academic…
Descriptors: Digital Literacy, Time Management, Structural Equation Models, Undergraduate Students
Schluchter, Thierry; Nagel, Siegfried; Valkanover, Stefan; Eckhart, Michael – Journal of Applied Research in Intellectual Disabilities, 2023
Background: Reciprocal relationships exist between motor competencies, physical activity and self-concept. Aims: Using a structural equation model, this study examined whether these relationships also appear in children with intellectual disabilities, how they can be validly measured, and if there are differences between children with and without…
Descriptors: Inclusion, Motor Development, Intellectual Disability, Physical Activity Level
Badie, Nasrin; Hussin, Ab Razak Che; Yadegaridehkordi, Elaheh; Singh, Dalbir; Lashkari, Arash Habibi – Education and Information Technologies, 2023
Cloud computing is the next generation of on-demand information technology services and products that deliver various applications over the Internet. Cloud computing is often adopted as a superior alternative by data centers to replace their current system. However, cloud computing services are still accompanied by many issues which hinder their…
Descriptors: Foreign Countries, Universities, Information Management, Information Storage
Wu, Sz-Yan; Kang, Hyeon-Ah; Jensen, Jody L. – Measurement in Physical Education and Exercise Science, 2023
The objective was to verify the construct validity and test-retest reliability of the Test of Advanced Movement Skills (TAMS) with an innovative dual-outcome scoring system. Three statistical approaches--confirmatory factor analysis (CFA), exploratory structural equation modeling (ESEM), and item response theory analysis (IRT)--were applied to the…
Descriptors: Construct Validity, Pretests Posttests, Psychomotor Skills, Scoring