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Franco-Martínez, Alicia; Alvarado, Jesús M.; Sorrel, Miguel A. – Educational and Psychological Measurement, 2023
A sample suffers range restriction (RR) when its variance is reduced comparing with its population variance and, in turn, it fails representing such population. If the RR occurs over the latent factor, not directly over the observed variable, the researcher deals with an indirect RR, common when using convenience samples. This work explores how…
Descriptors: Factor Analysis, Factor Structure, Scores, Sampling
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Hyunjung Lee; Heining Cham – Educational and Psychological Measurement, 2024
Determining the number of factors in exploratory factor analysis (EFA) is crucial because it affects the rest of the analysis and the conclusions of the study. Researchers have developed various methods for deciding the number of factors to retain in EFA, but this remains one of the most difficult decisions in the EFA. The purpose of this study is…
Descriptors: Factor Structure, Factor Analysis, Monte Carlo Methods, Goodness of Fit
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Fatih Orçan – International Journal of Assessment Tools in Education, 2025
Factor analysis is a statistical method to explore the relationships among observed variables and identify latent structures. It is crucial in scale development and validity analysis. Key factors affecting the accuracy of factor analysis results include the type of data, sample size, and the number of response categories. While some studies…
Descriptors: Factor Analysis, Factor Structure, Item Response Theory, Sample Size
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Lee, Bitna; Sohn, Wonsook – Educational and Psychological Measurement, 2022
A Monte Carlo study was conducted to compare the performance of a level-specific (LS) fit evaluation with that of a simultaneous (SI) fit evaluation in multilevel confirmatory factor analysis (MCFA) models. We extended previous studies by examining their performance under MCFA models with different factor structures across levels. In addition,…
Descriptors: Goodness of Fit, Factor Structure, Monte Carlo Methods, Factor Analysis
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Bang Quan Zheng; Peter M. Bentler – Structural Equation Modeling: A Multidisciplinary Journal, 2022
Chi-square tests based on maximum likelihood (ML) estimation of covariance structures often incorrectly over-reject the null hypothesis: [sigma] = [sigma(theta)] when the sample size is small. Reweighted least squares (RLS) avoids this problem. In some models, the vector of parameter must contain means, variances, and covariances, yet whether RLS…
Descriptors: Maximum Likelihood Statistics, Structural Equation Models, Goodness of Fit, Sample Size
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Montoya, Amanda K.; Edwards, Michael C. – Educational and Psychological Measurement, 2021
Model fit indices are being increasingly recommended and used to select the number of factors in an exploratory factor analysis. Growing evidence suggests that the recommended cutoff values for common model fit indices are not appropriate for use in an exploratory factor analysis context. A particularly prominent problem in scale evaluation is the…
Descriptors: Goodness of Fit, Factor Analysis, Cutting Scores, Correlation
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Koyuncu, Ilhan; Kilic, Abdullah Faruk – International Journal of Assessment Tools in Education, 2021
In exploratory factor analysis, although the researchers decide which items belong to which factors by considering statistical results, the decisions taken sometimes can be subjective in case of having items with similar factor loadings and complex factor structures. The aim of this study was to examine the validity of classifying items into…
Descriptors: Classification, Graphs, Factor Analysis, Decision Making
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Miroshnik, Kirill G.; Shcherbakova, Olga V.; Kaufman, James C. – Creativity Research Journal, 2022
Kaufman Domains of Creativity Scale (K-DOCS) is a self-report of creative behavior in five distinct domains. The present study aims to translate K-DOCS into Russian and evaluate its psychometric properties. The psychometric analysis was performed on a sample of adults recruited through Yandex Toloka (N = 1011; M[subscript age] = 35.94,…
Descriptors: Creativity Tests, Russian, Psychometrics, Foreign Countries
Clark, D. Angus; Bowles, Ryan P. – Grantee Submission, 2018
In exploratory item factor analysis (IFA), researchers may use model fit statistics and commonly invoked fit thresholds to help determine the dimensionality of an assessment. However, these indices and thresholds may mislead as they were developed in a confirmatory framework for models with continuous, not categorical, indicators. The present…
Descriptors: Factor Analysis, Goodness of Fit, Factor Structure, Monte Carlo Methods
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Rausch, Joseph R. – Applied Psychological Measurement, 2009
The investigation of change in factor structure over time can provide new opportunities for the development of theory in psychology. The method proposed to investigate change in intraindividual factor structure over time is an extension of P-technique factor analysis, in which the P-technique factor model is fit within relatively small windows of…
Descriptors: Monte Carlo Methods, Factor Structure, Factor Analysis, Item Response Theory
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Anderson, James C.; Gerbing, David W. – Psychometrika, 1984
This study of maximum likelihood confirmatory factor analysis found effects of practical significance due to sample size, the number of indicators per factor, and the number of factors for Joreskog and Sorbom's (1981) goodness-of-fit index (GFI), GFI adjusted for degrees of freedom, and the root mean square residual. (Author/BW)
Descriptors: Factor Analysis, Factor Structure, Goodness of Fit, Mathematical Models
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Roznowski, Mary; And Others – Educational and Psychological Measurement, 1994
A Monte Carlo investigation of simplex fitting as a method of determining the dimensionality of binary data matrices was conducted. Examination of the fit of correlation matrices with a known factor structure to correlation matrices that represent the perfect simplex shows that simplex fitting is a feasible approach under some circumstances. (SLD)
Descriptors: Correlation, Estimation (Mathematics), Factor Analysis, Factor Structure
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Kim, Sooyeon; Kyllonen, Patrick C. – ETS Research Report Series, 2006
The Standardized Letter of Recommendation (SLR), a 28-item form, was created by ETS to supplement the qualitative rating of graduate school applicants' nonacademic qualities with a quantitative approach. The purpose of this study was to evaluate the following psychometric properties of the SLR using the Rasch rating-scale model: dimensionality,…
Descriptors: Item Response Theory, Rating Scales, Data Analysis, Models
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Stricker, Lawrence J.; Rock, Donald A.; Lee, Yong-Won – ETS Research Report Series, 2005
This study assessed the factor structure of the LanguEdge™ test and the invariance of its factors across language groups. Confirmatory factor analyses of individual tasks and subsets of items in the four sections of the test, Listening, Reading, Speaking, and Writing, was carried out for Arabic-, Chinese-, and Spanish-speaking test takers. Two…
Descriptors: Factor Structure, Language Tests, Factor Analysis, Semitic Languages