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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
Canivez, Gary L.; Kush, Joseph C. – Journal of Psychoeducational Assessment, 2013
Weiss, Keith, Zhu, and Chen (2013a) and Weiss, Keith, Zhu, and Chen (2013b), this issue, report examinations of the factor structure of the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) and Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV), respectively; comparing Wechsler Hierarchical Model (W-HM) and…
Descriptors: Intelligence Tests, Factor Structure, Comparative Analysis, Arithmetic
Lee, Soon-Mook – International Journal of Testing, 2010
CEFA 3.02(Browne, Cudeck, Tateneni, & Mels, 2008) is a factor analysis computer program designed to perform exploratory factor analysis. It provides the main properties that are needed for exploratory factor analysis, namely a variety of factoring methods employing eight different discrepancy functions to be minimized to yield initial…
Descriptors: Factor Structure, Computer Software, Factor Analysis, Research Methodology
Jones-Farmer, L. Allison – Structural Equation Modeling: A Multidisciplinary Journal, 2010
When comparing latent variables among groups, it is important to first establish the equivalence or invariance of the measurement model across groups. Confirmatory factor analysis (CFA) is a commonly used methodological approach to examine measurement equivalence/invariance (ME/I). Within the CFA framework, the chi-square goodness-of-fit test and…
Descriptors: Factor Structure, Factor Analysis, Evaluation Research, Goodness of Fit

Hollenbeck, George P. – Educational and Psychological Measurement, 1972
The Little Jiffy" consists of principal components analysis and varimax rotation of all components with eigenvalues greater than one. (DG)
Descriptors: Cognitive Development, Comparative Analysis, Factor Analysis, Factor Structure

Terranova, Carmelo – Educational and Psychological Measurement, 1971
A computer program designed to compare factors from similar concept matrices (person by scale) obtained at different times is presented. (PR)
Descriptors: Attitude Change, Comparative Analysis, Computer Programs, Factor Structure

Hakstian, A. Ralph – Psychometrika, 1971
The oblimax, promax, maxplane, and Harris-Kaiser techniques are compared. (Author)
Descriptors: Comparative Analysis, Correlation, Factor Analysis, Factor Structure
Hofmann, Richard J. – 1973
A very general model for the computation of independent cluster solutions in factor analysis is presented. The model is discussed as being either orthogonal or oblique. Furthermore, it is demonstrated that for every orthogonal independent cluster solution there is an oblique analog. Using three illustrative examples, certain generalities are made…
Descriptors: Cluster Analysis, Comparative Analysis, Factor Analysis, Factor Structure

Zwick, William R.; Velicer, Wayne F. – 1984
A common problem in the behavioral sciences is to determine if a set of observed variables can be more parsimoniously represented by a smaller set of derived variables. To address this problem, the performance of five methods for determining the number of components to retain (Horn's parallel analysis, Velicer's Minimum Average Partial (MAP),…
Descriptors: Behavioral Science Research, Comparative Analysis, Correlation, Data Interpretation
Byrne, Barbara M. – 1994
Working from a common data base and hypothesized model, this paper demonstrates and compares the EQS and LISREL computer program strategies in the analysis of a second-order factor model. Program similarities and differences are noted with respect to: (1) preliminary analyses of the data; (2) treatment of data that are not multivariately normal;…
Descriptors: Adolescents, Comparative Analysis, Computer Oriented Programs, Computer Software

Wiseman, Michael; Bogner, Franz X. – Scandinavian Journal of Educational Research, 1997
The perceptions of students toward conservation and nature utilization and their behavior toward the environment were studied with 725 Danish adolescents and a previously studied group of Bavarian adolescents. Following construct validation, comparison of mean within-region factor values reveals substantial differences between countries. (SLD)
Descriptors: Adolescents, Behavior Patterns, Child Development, Comparative Analysis