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Finkbeiner, C. T.; Tucker, L. R. – Psychometrika, 1982
The residual variance is often used as an approximation to the uniqueness in factor analysis. An upper bound approximation to the residual variance is presented for the case when the correlation matrix is singular. (Author/JKS)
Descriptors: Algorithms, Correlation, Factor Analysis, Matrices
Peer reviewed Peer reviewed
Hafner, Robert – Psychometrika, 1981
The method proposed by Harman and Fukuda to treat the so-called Heywood case in the minres method in factor analysis (i.e., the case where the resulting communalities are greater than one) involves the frequent solution of eigenvalue problems. A simple method to treat this problem is presented. (Author/JKS)
Descriptors: Algorithms, Data Analysis, Factor Analysis
Peer reviewed Peer reviewed
ten Berge, Jos M. F.; And Others – Psychometrika, 1981
Several algorithms for computing the greatest lower bound to reliability or the constrained minimum-trace communality solution in factor analysis have been developed. The convergence properties of these methods are examined. A uniqueness proof for the desired solution is offered. (Author/JKS)
Descriptors: Algorithms, Factor Analysis, Test Reliability
Peer reviewed Peer reviewed
Okamoto, Masashi; Ihara, Masamori – Psychometrika, 1983
A new algorithm to obtain the least squares solution in common factor analysis is presented. It is based on the up-and-down Marquadt algorithm developed by the present authors. Experiments in the use of the algorithm under various conditions are discussed. (Author/JKS)
Descriptors: Algorithms, Factor Analysis, Least Squares Statistics, Mathematical Models
Peer reviewed Peer reviewed
Lee, Sik-Yum – Psychometrika, 1981
Confirmatory factor analysis is considered from a Bayesian viewpoint, in which prior information concerning parameters is incorporated in the analysis. An interactive algorithm is developed to obtain the Bayesian estimates. A numerical example is presented. (Author/JKS)
Descriptors: Algorithms, Bayesian Statistics, Factor Analysis, Maximum Likelihood Statistics
Peer reviewed Peer reviewed
Kiers, Henk A. L.; ten Berge, Jos M. F. – Psychometrika, 1989
Two alternating least squares algorithms are presented for the simultaneous components analysis method of R. E. Millsap and W. Meredith (1988). These methods, one for small data sets and one for large data sets, can indicate whether or not a global optimum for the problem has been attained. (SLD)
Descriptors: Algorithms, Factor Analysis, Least Squares Statistics, Statistical Analysis
Peer reviewed Peer reviewed
Kiers, Henk A. L. – Psychometrika, 1994
A class of oblique rotation procedures is proposed to rotate a pattern matrix so that it optimally resembles a matrix that has an exact simple pattern. It is demonstrated that the method can recover relatively complex simple structures where other simple structure rotation techniques fail. (SLD)
Descriptors: Algorithms, Factor Analysis, Factor Structure, Matrices
Peer reviewed Peer reviewed
Boik, Robert J. – Psychometrika, 1996
Joint correspondence analysis is a technique for constructing reduced-dimensional representations of pairwise relationships among categorical variables. An alternating least-squares algorithm for conducting joint correspondence analysis is presented that requires fewer iterations than the algorithm previously proposed by M. J. Greenacre. (SLD)
Descriptors: Algorithms, Equations (Mathematics), Factor Analysis, Least Squares Statistics
Peer reviewed Peer reviewed
Nevels, Klaas – Psychometrika, 1989
In FACTALS, an alternating least squares algorithm is used to fit the common factor analysis model to multivariate data. A. Mooijaart (1984) demonstrated that the algorithm is based on an erroneous assumption. This paper gives a proper solution for the loss function used in FACTALS. (Author/TJH)
Descriptors: Algorithms, Factor Analysis, Goodness of Fit, Least Squares Statistics
Peer reviewed Peer reviewed
Goldberger, Arthur S.; Joreskog, Karl G. – Psychometrika, 1972
Descriptors: Algorithms, Factor Analysis, Least Squares Statistics, Mathematical Models
Peer reviewed Peer reviewed
Shapiro, Alexander – Psychometrika, 1982
Minimum trace factor analysis has been used to find the greatest lower bound to reliability. This technique, however, fails to be scale free. A solution to the scale problem is proposed through the maximization of the greatest lower bound as the function of weights. (Author/JKS)
Descriptors: Algorithms, Estimation (Mathematics), Factor Analysis, Psychometrics
Peer reviewed Peer reviewed
Tisak, John; Meredith, William – Psychometrika, 1989
A longitudinal factor analysis model that is entirely exploratory is proposed for use with multiple populations. Factorial collapse, period/practice effects, and an invariant and/or stationary factor pattern are allowed. The model is formulated stochastically and implemented via a stage-wise EM algorithm. (TJH)
Descriptors: Algorithms, Factor Analysis, Longitudinal Studies, Maximum Likelihood Statistics
Peer reviewed Peer reviewed
ten Berge, Jos M. F.; Kiers, Henk A. L. – Psychometrika, 1989
The DEDICOM (decomposition into directional components) model provides a framework for analyzing square but asymmetric matrices of directional relationships among "n" objects or persons in terms of a small number of components. One version of DEDICOM ignores the diagonal entries of the matrices. A straightforward computational solution…
Descriptors: Algorithms, Factor Analysis, Goodness of Fit, Least Squares Statistics
Peer reviewed Peer reviewed
Harper, Dean – Psychometrika, 1972
A procedure is outlined showing how the axiom of local independence for latent structure models can be weakened. (CK)
Descriptors: Algorithms, Factor Analysis, Factor Structure, Mathematical Applications
Peer reviewed Peer reviewed
Schonemann, Peter H.; Wang, Ming-Mei – Psychometrika, 1972
Relations between maximum likelihood factor analysis and factor indeterminacy are discussed. (CK)
Descriptors: Algorithms, Correlation, Factor Analysis, Factor Structure
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