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Kentaro Hayashi; Ke-Hai Yuan; Peter M. Bentler – Grantee Submission, 2025
Most existing studies on the relationship between factor analysis (FA) and principal component analysis (PCA) focus on approximating the common factors by the first few components via the closeness between their loadings. Based on a setup in Bentler and de Leeuw (Psychometrika 76:461-470, 2011), this study examines the relationship between FA…
Descriptors: Factor Analysis, Comparative Analysis, Correlation, Evaluation Criteria
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Yan Xia; Xinchang Zhou – Educational and Psychological Measurement, 2025
Parallel analysis has been considered one of the most accurate methods for determining the number of factors in factor analysis. One major advantage of parallel analysis over traditional factor retention methods (e.g., Kaiser's rule) is that it addresses the sampling variability of eigenvalues obtained from the identity matrix, representing the…
Descriptors: Factor Analysis, Statistical Analysis, Evaluation Methods, Sampling
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Julia-Kim Walther; Martin Hecht; Steffen Zitzmann – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Small sample sizes pose a severe threat to convergence and accuracy of between-group level parameter estimates in multilevel structural equation modeling (SEM). However, in certain situations, such as pilot studies or when populations are inherently small, increasing samples sizes is not feasible. As a remedy, we propose a two-stage regularized…
Descriptors: Sample Size, Hierarchical Linear Modeling, Structural Equation Models, Matrices
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Olvera Astivia, Oscar L. – Measurement: Interdisciplinary Research and Perspectives, 2021
Partially specified correlation matrices (not to be confused with matrices with missing data or EM-correlation matrices) can appear in research settings such as integrative data analyses, quantitative systematic reviews or whenever the study design only allows for the collection of certain variables. Although approaches to fill in these missing…
Descriptors: Correlation, Matrices, Statistical Analysis, Research Problems
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Beauducel, André; Hilger, Norbert – Educational and Psychological Measurement, 2021
Methods for optimal factor rotation of two-facet loading matrices have recently been proposed. However, the problem of the correct number of factors to retain for rotation of two-facet loading matrices has rarely been addressed in the context of exploratory factor analysis. Most previous studies were based on the observation that two-facet loading…
Descriptors: Factor Analysis, Statistical Analysis, Correlation, Models
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Albreiki, Balqis; Habuza, Tetiana; Zaki, Nazar – International Journal of Educational Technology in Higher Education, 2023
Technological advances have significantly affected education, leading to the creation of online learning platforms such as virtual learning environments and massive open online courses. While these platforms offer a variety of features, none of them incorporates a module that accurately predicts students' academic performance and commitment.…
Descriptors: Identification, At Risk Students, Artificial Intelligence, Academic Achievement
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Masaki Goda; Shinichi Kishizawa; Yamato Hasegawa – Physical Review Physics Education Research, 2025
In this paper, we describe student understanding of the "force concept" (basic concepts of Newtonian mechanics) by representing it as a vector-valued quantity, which we refer to as the "score-state vector," in a (30-dimensional) Force Concept Inventory (FCI) score space. We use a large ensemble of FCI results collected…
Descriptors: Mechanics (Physics), Scientific Concepts, Scientific Literacy, Foreign Countries
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Paul A. Jewsbury; Matthew S. Johnson – Large-scale Assessments in Education, 2025
The standard methodology for many large-scale assessments in education involves regressing latent variables on numerous contextual variables to estimate proficiency distributions. To reduce the number of contextual variables used in the regression and improve estimation, we propose and evaluate principal component analysis on the covariance matrix…
Descriptors: Factor Analysis, Matrices, Regression (Statistics), Educational Assessment
Marcus A. Fagan – ProQuest LLC, 2020
Previous research has individually assessed parallel analysis and minimum average partial for factor retention in exploratory factor analysis using ordinal variables. The current study is a comprehensive simulation study including the manipulation of eight conditions (type of correlation matrix, sample size, number of variables per factor, number…
Descriptors: Retention (Psychology), Factor Analysis, Correlation, Matrices
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McFarland, Dennis – Journal of Intelligence, 2020
Network models of the WAIS-IV based on regularized partial correlation matrices have been reported to outperform latent variable models based on uncorrected correlation matrices. The present study sought to compare network and latent variable models using both partial and uncorrected correlation matrices with both types of models. The results show…
Descriptors: Correlation, Matrices, Adults, Intelligence Tests
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Özdemir, Hasan Fehmi; Toraman, Çetin; Kutlu, Ömer – Turkish Journal of Education, 2019
No matter how strong the theoretical infrastructure of a study is, if the measurement instruments do not have the necessary psychometric qualities, there will be a question of trust in interpreting the findings, and it will be inevitable to make wrong decisions with the results. One of the important steps in scale development/adaptation studies is…
Descriptors: Correlation, Matrices, Construct Validity, Likert Scales
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Rahayu, Sri; Sugiarto, Teguh; Madu, Ludiro; Holiawati; Subagyo, Ahmad – International Journal of Educational Methodology, 2017
This study aims to apply the model principal component analysis to reduce multicollinearity on variable currency exchange rate in eight countries in Asia against US Dollar including the Yen (Japan), Won (South Korea), Dollar (Hong Kong), Yuan (China), Bath (Thailand), Rupiah (Indonesia), Ringgit (Malaysia), Dollar (Singapore). It looks at yield…
Descriptors: Foreign Countries, Factor Analysis, Multiple Regression Analysis, Correlation
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Hedges, Larry V. – Research Synthesis Methods, 2016
Structural equation models play an important role in the social sciences. Consequently, there is an increasing use of meta-analytic methods to combine evidence from studies that estimate the parameters of structural equation models. Two approaches are used to combine evidence from structural equation models: A direct approach that combines…
Descriptors: Meta Analysis, Structural Equation Models, Social Science Research, Research Methodology
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Vernizzi, Graziano; Nakai, Miki – Sociological Methods & Research, 2015
It is well known that a categorical random variable can be represented geometrically by a simplex. Accordingly, several measures of association between categorical variables have been proposed and discussed in the literature. Moreover, the standard definitions of covariance and correlation coefficient for continuous random variables have been…
Descriptors: Matrices, Geometry, Statistical Analysis, Correlation
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Dombrowski, Stefan C.; McGill, Ryan J.; Canivez, Gary L. – School Psychology Quarterly, 2018
The Woodcock-Johnson (fourth edition; WJ IV; Schrank, McGrew, & Mather, 2014a) was recently redeveloped and retains its linkage to Cattell-Horn-Carroll theory (CHC). Independent reviews (e.g., Canivez, 2017) and investigations (Dombrowski, McGill, & Canivez, 2017) of the structure of the WJ IV full test battery and WJ IV Cognitive have…
Descriptors: Factor Analysis, Achievement Tests, Cognitive Tests, Cognitive Ability
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