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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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Kelvin T. Afolabi; Timothy R. Konold – Practical Assessment, Research & Evaluation, 2024
Exploratory structural equation (ESEM) has received increased attention in the methodological literature as a promising tool for evaluating latent variable measurement models. It overcomes many of the limitations attached to exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), while capitalizing on the benefits of each. Given…
Descriptors: Measurement Techniques, Factor Analysis, Structural Equation Models, Comparative Analysis
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Karl Schweizer; Andreas Gold; Dorothea Krampen; Stefan Troche – Educational and Psychological Measurement, 2024
Conceptualizing two-variable disturbances preventing good model fit in confirmatory factor analysis as item-level method effects instead of correlated residuals avoids violating the principle that residual variation is unique for each item. The possibility of representing such a disturbance by a method factor of a bifactor measurement model was…
Descriptors: Correlation, Factor Analysis, Measurement Techniques, Item Analysis
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Lingbo Tong; Wen Qu; Zhiyong Zhang – Grantee Submission, 2025
Factor analysis is widely utilized to identify latent factors underlying the observed variables. This paper presents a comprehensive comparative study of two widely used methods for determining the optimal number of factors in factor analysis, the K1 rule, and parallel analysis, along with a more recently developed method, the bass-ackward method.…
Descriptors: Factor Analysis, Monte Carlo Methods, Statistical Analysis, Sample Size
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Tenko Raykov; Christine DiStefano; Lisa Calvocoressi – Educational and Psychological Measurement, 2024
This note demonstrates that the widely used Bayesian Information Criterion (BIC) need not be generally viewed as a routinely dependable index for model selection when the bifactor and second-order factor models are examined as rival means for data description and explanation. To this end, we use an empirically relevant setting with…
Descriptors: Bayesian Statistics, Models, Decision Making, Comparative Analysis
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André Beauducel; Norbert Hilger; Tobias Kuhl – Educational and Psychological Measurement, 2024
Regression factor score predictors have the maximum factor score determinacy, that is, the maximum correlation with the corresponding factor, but they do not have the same inter-correlations as the factors. As it might be useful to compute factor score predictors that have the same inter-correlations as the factors, correlation-preserving factor…
Descriptors: Scores, Factor Analysis, Correlation, Predictor Variables
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Tenko Raykov – Structural Equation Modeling: A Multidisciplinary Journal, 2024
This note demonstrates that measurement invariance does not guarantee meaningful and valid group comparisons in multiple-population settings. The article follows on a recent critical discussion by Robitzsch and Lüdtke, who argued that measurement invariance was not a pre-requisite for such comparisons. Within the framework of common factor…
Descriptors: Error of Measurement, Prerequisites, Factor Analysis, Evaluation Methods
Christopher E. Shank – ProQuest LLC, 2024
This dissertation compares the performance of equivalence test (EQT) and null hypothesis test (NHT) procedures for identifying invariant and noninvariant factor loadings under a range of experimental manipulations. EQT is the statistically appropriate approach when the research goal is to find evidence of group similarity rather than group…
Descriptors: Factor Analysis, Goodness of Fit, Intervals, Comparative Analysis
Klauth, Bo – ProQuest LLC, 2023
In conducting confirmatory factor analysis with ordered response items, the literature suggests that when the number of responses is five and item skewness (IS) is approximately normal, researchers can employ maximum likelihood with robust standard errors (MLR). However, MLR can yield biased factor loadings (FL) and FL standard errors (FLSE) when…
Descriptors: Item Response Theory, Evaluation Methods, Factor Analysis, Error of Measurement
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Teck Kiang Tan – Practical Assessment, Research & Evaluation, 2024
The procedures of carrying out factorial invariance to validate a construct were well developed to ensure the reliability of the construct that can be used across groups for comparison and analysis, yet mainly restricted to the frequentist approach. This motivates an update to incorporate the growing Bayesian approach for carrying out the Bayesian…
Descriptors: Bayesian Statistics, Factor Analysis, Programming Languages, Reliability
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Markus T. Jansen; Ralf Schulze – Educational and Psychological Measurement, 2024
Thurstonian forced-choice modeling is considered to be a powerful new tool to estimate item and person parameters while simultaneously testing the model fit. This assessment approach is associated with the aim of reducing faking and other response tendencies that plague traditional self-report trait assessments. As a result of major recent…
Descriptors: Factor Analysis, Models, Item Analysis, Evaluation Methods
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Yu, Cheryl; Liu, Wei; Waller, Stephane – Perspectives: Policy and Practice in Higher Education, 2023
China is a major source country of students in the UK's taught Master's programs. The reliance on China as a major source country has caused some concerns over its sustainability. Will the Chinese students continue to come? To answer this question, a push-pull factor analysis is conducted on the perceptions of Chinese students who graduated from…
Descriptors: Foreign Countries, Study Abroad, Foreign Students, College Graduates
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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
Thayer Trenhaile – ProQuest LLC, 2023
The purpose of this study was to examine whether there was a statistically significant (p < 0.05) difference in student-athletes' resilience by whether they attended religious or secular higher education institutions. The study utilized data from the 2018 Multi-Institutional Study of Leadership (MSL) survey, which was completed by 8,163…
Descriptors: Religious Colleges, Resilience (Psychology), Comparative Analysis, Institutional Characteristics
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Seyda Aydin-Karaca; Mustafa Serdar Köksal; Bilkay Bi – Journal of Psychoeducational Assessment, 2024
This study aimed to develop a parent rating scale (PRSG) for screening children for further identification process in terms of giftedness. The participants of the study were 255 parents of gifted and non-gifted students. The PRSG, consisting of 30 items, was created by consulting parents and reviewing instruments existent in the literature. As…
Descriptors: Rating Scales, Parent Attitudes, Scores, Comparative Analysis
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