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Hanafi, Mohamed; ten Berge, Jos M. F. – Psychometrika, 2003
It is known that the Maxbet algorithm, which is an alternative to the method of generalized canonical correlation analysis and Procrustes analysis, may converge to local maxima. Discusses an eigenvalue criterion that is sufficient, but not necessary, for global optimality of the successive Maxbet algorithm. (SLD)
Descriptors: Algorithms, Correlation
Peer reviewed Peer reviewed
Leeuw, Jan De – Psychometrika, 1982
A formula for the determinant of a partitioned matrix, possibly with singular submatrices, is derived and applied to some psychometric and numerical problems. (Author)
Descriptors: Algorithms, Matrices, Statistical Studies
Peer reviewed Peer reviewed
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
Dolker, Michael; And Others – Psychometrika, 1982
Efron's Monte Carlo bootstrap algorithm is shown to cause degeneracies in Pearson's r for sufficiently small samples. Two ways of preventing this problem when programing the bootstrap of r are considered. (Author)
Descriptors: Algorithms, Computer Programs, Correlation, Sampling
Peer reviewed Peer reviewed
Clarkson, Douglas B.; Gonzalez, Richard – Psychometrika, 2001
Defines a random effects diagonal metric multidimensional scaling model, gives its computational algorithms, describes researchers' experiences with these algorithms, and provides an illustration of the use of the model and algorithms. (Author/SLD)
Descriptors: Algorithms, Mathematical Models, Multidimensional Scaling
Peer reviewed Peer reviewed
Jennrich, Robert I. – Psychometrika, 2001
Identifies a general algorithm for orthogonal rotation and shows that when an algorithm parameter alpha is sufficiently large, the algorithm converges monotonically to a stationary point of the rotation criterion from any starting value. Introduces a modification that does not require a large alpha and discusses the use of this modification as a…
Descriptors: Algorithms, Factor Structure, Orthogonal Rotation
Peer reviewed Peer reviewed
Leenen, Iwin; Van Mechelen, Iven; De Boeck, Paul; Rosenberg, Seymour – Psychometrika, 1999
Presents a three-way, three-mode extension of the two-way, two-mode hierarchical classes model of P. De Boeck and S. Rosenberg (1998) for the analysis of individual differences in binary object x attribute arrays. Illustrates the model with data on psychiatric diagnosis and discusses the relation between the model and other extant models. (SLD)
Descriptors: Algorithms, Individual Differences, Models, Set Theory
Peer reviewed Peer reviewed
Arminger, Gerhard; Muthen, Bengt O. – Psychometrika, 1998
Nonlinear latent variable models are specified that include quadratic forms and interactions of latent regressor variable as special cases. To estimate the parameters, the models are put in a Bayesian framework with conjugate priors for the parameters. The proposed estimation methods are illustrated by two simulation studies. (SLD)
Descriptors: Algorithms, Bayesian Statistics, Estimation (Mathematics), Mathematical Models
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Brusco, Michael J.; Stahl, Stephanie – Psychometrika, 2001
Describes an interactive procedure for multiobjective asymmetric unidimensional seriation problems that uses a dynamic-programming algorithm to generate partially the efficient set of sequences for small to medium-sized problems and a multioperational heuristic to estimate the efficient set for larger problems. Applies the procedure to an…
Descriptors: Algorithms, Data Analysis, Estimation (Mathematics), Heuristics
Peer reviewed Peer reviewed
Ferligoj, Anuska; Batagelj, Vladimir – Psychometrika, 1982
Using constraints with cluster analysis limits the possible number of clusters. This paper deals with clustering problems where grouping is constrained by a symmetric and reflexive relation. Two approaches, along with illustrations, are presented. (Author/JKS)
Descriptors: Algorithms, Cluster Analysis, Data Analysis, Mathematical Models
Peer reviewed Peer reviewed
Commandeur, Jacques J. F.; Groenen, Patrick J. F.; Meulman, Jacqueline J. – Psychometrika, 1999
Presents two methods for including weights in distance-based nonlinear multivariate data analysis. One method assigns weights to the objects, while the other is concerned with differential weighing of groups of variables. Discusses applications of these weighting schemes and proposed an algorithm to minimize the corresponding loss function. (SLD)
Descriptors: Algorithms, Multidimensional Scaling, Multivariate Analysis, Research Methodology