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Tugay Kaçak; Abdullah Faruk Kiliç – International Journal of Assessment Tools in Education, 2025
Researchers continue to choose PCA in scale development and adaptation studies because it is the default setting and overestimates measurement quality. When PCA is utilized in investigations, the explained variance and factor loadings can be exaggerated. PCA, in contrast to the models given in the literature, should be investigated in…
Descriptors: Factor Analysis, Monte Carlo Methods, Mathematical Models, Sample Size

van der Heijden, Peter G. M.; Worsley, Keith J. – Psychometrika, 1988
With reference to the authors' previous paper (1985), it is proposed that loglinear analysis can be used to detect interactions in a multiway contingency table and explore the form of these interactions with correspondence analysis. Correspondence analysis assists in finding a model with restrictions on the interaction parameters. (TJH)
Descriptors: Factor Analysis, Mathematical Models, Research Methodology, Set Theory
Horst, Paul – 1970
In the traditional Guttman-Harris type image analysis, a transformation is applied to the data matrix such that each column of the transformed data matrix is the best least squares estimate of the corresponding column of the data matrix from the remaining columns. The model is scale free. However, it assumes (1) that the correlation matrix is…
Descriptors: Correlation, Factor Analysis, Mathematical Models, Research Methodology

Maraun, Michael D.; And Others – Multivariate Behavioral Research, 1996
The issue of indeterminacy in factor analysis and the debate between the proposed alternative solution and posterior moment position are explored in an article and 14 commentaries and rebuttals in two rounds. Implications for applied work involving factor analysis are discussed. (SLD)
Descriptors: Factor Analysis, Factor Structure, Mathematical Models, Metaphors
Hester, Yvette – 1996
Data reduction techniques seek to combine variables that account for patterns of variation in observed dependent variables in such a way that a simpler model is available for analysis. Factor analysis is a data reduction technique that attempts to model or explain a set of variables in terms of their associations. To understand why this technique…
Descriptors: Factor Analysis, Factor Structure, Heuristics, Mathematical Models

Buss, Allan R. – Developmental Psychology, 1974
The concepts of quantitative and structural change are considered from a multivariate perspective. A hybrid of these two types of change, quantistructural change, is described. (CS)
Descriptors: Developmental Psychology, Factor Analysis, Mathematical Models, Multivariate Analysis

Farr, S. David – American Educational Research Journal, 1971
Descriptors: Data Analysis, Factor Analysis, Mathematical Models, Research Methodology

Tanaka, Yutaka; Odaka, Yoshimasa – Psychometrika, 1989
A method is proposed for detecting influential observations in iterative principal factor analysis. Theoretical influence functions are derived for two components of the common variance decomposition. The major mathematical tool is the influence function derived by Tanaka (1988). (SLD)
Descriptors: Equations (Mathematics), Factor Analysis, Mathematical Models, Research Methodology
Draper, John F., Jr. – 1972
The applicability of the Analysis of Variance, ANOVA, procedures to the analysis of dichotomous repeated measure data is described. The design models for which data were simulated in this investigation were chosen to represent simple cases of two experimental situations: situation one, in which subjects' responses to a single randomly selected set…
Descriptors: Analysis of Variance, Factor Analysis, Mathematical Models, Research Methodology

Cohen, Jacob – Educational and Psychological Measurement, 1973
Comments based on J. J. Kennedy's The eta coefficient in complex ANOVA designs,'' EJ 031 388. (CB)
Descriptors: Analysis of Variance, Factor Analysis, Mathematical Models, Measurement Techniques

Schmidt, William H.; Scheifley, Verda – American Educational Research Journal, 1973
Descriptors: Analysis of Covariance, Factor Analysis, Mathematical Models, Nonparametric Statistics

Goldberger, Arthur S. – Psychometrika, 1971
Several themes which are common to both econometrics and psychometrics are surveyed. The themes are illustrated by reference to permanent income hypotheses, simultaneous equation models, adaptive expectations and partial adjustment schemes, and by reference to test score theory, factor analysis, and time-series models. (Author)
Descriptors: Economics, Factor Analysis, Mathematical Models, Multiple Regression Analysis

Froemel, Ernest C. – Psychometrika, 1971
Saunder's routine, Buhler's empirical approximation, and Castellan's series expansion are compared. Saunder's routine was identified as an acceptably accurate method. (PR)
Descriptors: Comparative Analysis, Computer Programs, Correlation, Factor Analysis
Jurs, Stephen; And Others – 1993
The scree test and its linear regression technique are reviewed, and results of its use in factor analysis and Delphi data sets are described. The scree test was originally a visual approach for making judgments about eigenvalues, which considered the relationships of the eigenvalues to one another as well as their actual values. The graph that is…
Descriptors: Delphi Technique, Equations (Mathematics), Factor Analysis, Graphs

Rindskopf, David – Contemporary Educational Psychology, 1984
Statistical methods, called latent variable models, have been developed to provide rigorous tests of theories involving unobserved variables. This paper describes the major types of latent variable models, shows how they can be applied in educational research, and gives representative examples of their use from the literature. (Author/BW)
Descriptors: Factor Analysis, Hypothesis Testing, Latent Trait Theory, Mathematical Models