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Julia-Kim Walther; Martin Hecht; Benjamin Nagengast; Steffen Zitzmann – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A two-level data set can be structured in either long format (LF) or wide format (WF), and both have corresponding SEM approaches for estimating multilevel models. Intuitively, one might expect these approaches to perform similarly. However, the two data formats yield data matrices with different numbers of columns and rows, and their "cols :…
Descriptors: Data, Monte Carlo Methods, Statistical Distributions, Matrices
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
Schneider, W. Joel – Journal of Psychoeducational Assessment, 2013
Researchers often argue that the structural models of the constructs they study are relevant to clinicians. Unfortunately, few clinicians are able to translate the mathematically precise relationships between latent constructs and observed scores into information that can be usefully applied to individuals. Typically this means that when a new…
Descriptors: Factor Analysis, Psychological Studies, Cognitive Ability, Test Reliability
Adachi, Kohei – Psychometrika, 2009
In component analysis solutions, post-multiplying a component score matrix by a nonsingular matrix can be compensated by applying its inverse to the corresponding loading matrix. To eliminate this indeterminacy on nonsingular transformation, we propose Joint Procrustes Analysis (JPA) in which component score and loading matrices are simultaneously…
Descriptors: Simulation, Matrices, Factor Analysis, Mathematics
Boik, Robert J. – Psychometrika, 2008
In this paper implicit function-based parameterizations for orthogonal and oblique rotation matrices are proposed. The parameterizations are used to construct Newton algorithms for minimizing differentiable rotation criteria applied to "m" factors and "p" variables. The speed of the new algorithms is compared to that of existing algorithms and to…
Descriptors: Criteria, Factor Analysis, Mathematics, Matrices
The Harris-Kaiser Independent Cluster Rotation as a Method for Rotation to Simple Component Weights.
Peer reviewedKiers, H. A. L.; ten Berge, Jos M. F. – Psychometrika, 1994
Procedures for oblique rotation of factors or principal components typically focus on rotating the pattern matrix so that it becomes optimally simple. How the Harris and Kaiser independent cluster (1964) rotation can be modified to obtain a simple weights matrix rather than a simple pattern is described and illustrated. (SLD)
Descriptors: Equations (Mathematics), Factor Analysis, Matrices
Peer reviewedTrendafilov, Nickolay T. – Multivariate Behavioral Research, 1994
An alternative to the PROMAX exploratory method is presented for constructing a target matrix in Procrustean rotation in factor analysis. A technique is proposed based on vector majorization. The approach is illustrated with several standard numerical examples. (SLD)
Descriptors: Equations (Mathematics), Factor Analysis, Factor Structure, Matrices
Peer reviewedBrowne, Michael W. – Psychometrika, 1992
Structural models that yield circumplex inequality patterns are reviewed, focusing on a model developed by T. W. Anderson (1960). A modification is proposed to this model to allow for negative correlations. This model may be reparameterized as a factor analysis model with nonlinear constraints on the factor loadings. (SLD)
Descriptors: Correlation, Equations (Mathematics), Factor Analysis, Graphs
Asparouhov, Tihomir; Muthen, Bengt – Structural Equation Modeling: A Multidisciplinary Journal, 2009
Exploratory factor analysis (EFA) is a frequently used multivariate analysis technique in statistics. Jennrich and Sampson (1966) solved a significant EFA factor loading matrix rotation problem by deriving the direct Quartimin rotation. Jennrich was also the first to develop standard errors for rotated solutions, although these have still not made…
Descriptors: Structural Equation Models, Testing, Factor Analysis, Research Methodology
Peer reviewedten Berge, Jos M. F.; Kiers, Henk A. L. – Psychometrika, 1993
R. A. Bailey and J. C. Gower explored approximating a symmetric matrix "B" by another, "C," in the least squares sense when the squared discrepancies for diagonal elements receive specific nonunit weights. A solution is proposed where "C" is constrained to be positive semidefinite and of a fixed rank. (SLD)
Descriptors: Algorithms, Equations (Mathematics), Factor Analysis, Least Squares Statistics
Peer reviewedter Braak, Cajo J. F. – Psychometrika, 1990
Canonical weights and structure correlations are used to construct low dimensional views of the relationships between two sets of variables. These views, in the form of biplots, display familiar statistics: correlations between pairs of variables, and regression coefficients. (SLD)
Descriptors: Correlation, Data Interpretation, Equations (Mathematics), Factor Analysis
Peer reviewedKiers, Henk A. L. – Psychometrika, 1991
Several methods for the analysis of three-way data (data classified three ways) are described and shown to be variants of principal components analysis of the two-way supermatrix in which each two-way slice is strung out into a column vector. Direct fitting and fitting derived data are considered. (SLD)
Descriptors: Equations (Mathematics), Evaluation Methods, Factor Analysis, Goodness of Fit
Peer reviewedKaiser, Henry F.; Derflinger, Gerhard – Applied Psychological Measurement, 1990
The fundamental mathematical model of L. L. Thurstone's common factor analysis is reviewed, and basic covariance matrices of maximum likelihood factor analysis and alpha factor analysis are presented. The methods are compared in terms of computational and scaling contrasts. Weighting and the appropriate number of common factors are considered.…
Descriptors: Comparative Analysis, Equations (Mathematics), Factor Analysis, Mathematical Models
Peer reviewedNoma, Elliot – Journal of the American Society for Information Science, 1984
Argues that co-citation methods combine citing behavior of authors by assuming they share common view of scientific literature which affects assessments of dimensionality and clustering of articles. Co-citation matrices, effects of shared point-of-view assumption, and co-citation compared with bibliographic coupling and centroid scaling are…
Descriptors: Bibliographic Coupling, Citations (References), Cluster Analysis, Cluster Grouping
Peer reviewedPham, Tuan Dinh; Mocks, Joachim – Psychometrika, 1992
Sufficient conditions are derived for the consistency and asymptotic normality of the least squares estimator of a trilinear decomposition model for multiway data analysis. The limiting covariance matrix is computed. (Author/SLD)
Descriptors: Equations (Mathematics), Estimation (Mathematics), Factor Analysis, Least Squares Statistics

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