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Ponocny, Ivo – Psychometrika, 2000
Introduces a new algorithm for obtaining exact person fit indexes for the Rasch model. The algorithm realizes most tests for a general family of alternative hypotheses, including tests concerning differential item functioning. The method is also used as a goodness-of-fit test in some circumstances. Simulated examples and an empirical investigation…
Descriptors: Algorithms, Goodness of Fit, Item Bias, Simulation
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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
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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
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DeSarbo, Wayne S.; And Others – Psychometrika, 1990
A nonspatial operationalization of the Krumhansl distance-density model of similarity is presented. The conceptual model and empirical evidence are reviewed. A nonspatial, tree-fitting methodology is described, which is sufficiently flexible to fit several competing hypotheses of similarity formation. Extensions to spatial models, three-way…
Descriptors: Algorithms, Cluster Analysis, Goodness of Fit, Mathematical Models
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Lingoes, James C.; Schonemann, Peter H. – Psychometrika, 1974
Descriptors: Algorithms, Goodness of Fit, Matrices, Orthogonal Rotation
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Bock, R. Darrell; Aitkin, Murray – Psychometrika, 1981
The practicality of using the EM algorithm for maximum likelihood estimation of item parameters in the marginal distribution is presented. The EM procedure is shown to apply to general item-response models. (Author/JKS)
Descriptors: Algorithms, Factor Analysis, Goodness of Fit, Item Analysis
Peer reviewed Peer reviewed
Hubert, Lawrence – Psychometrika, 1973
The present paper discusses two rather different types of partitioning techniques that still have the same property of monotone invariance. (Author)
Descriptors: Algorithms, Cluster Analysis, Cluster Grouping, Goodness of Fit
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Hubert, Lawrence – Psychometrika, 1972
Paper is an attempt to extend the hierarchical partitioning algorithms and to emphasize a general connection between these clustering procedures and the mathematical theory of lattices. (Author)
Descriptors: Algorithms, Cluster Grouping, Goodness of Fit, Mathematical Applications
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Polson, Peter G.; Huizinga, David – Psychometrika, 1974
Descriptors: Algorithms, Computer Programs, Goodness of Fit, Learning Processes
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Kiers, Henk A. L. – Psychometrika, 1997
A general approach for fitting a model to a data matrix by weighted least squares (WLS) is studied. The approach consists of iteratively performing steps of existing algorithms for ordinary least squares fitting of the same model and is based on maximizing a function that majorizes WLS loss function. (Author/SLD)
Descriptors: Algorithms, Goodness of Fit, Least Squares Statistics, Mathematical Models
Peer reviewed Peer reviewed
Kiers, Henk A. L. – Psychometrika, 1989
An alternating least squares algorithm is offered for fitting the DEcomposition into DIrectional COMponents (DEDICOM) model for representing asymmetric relations among a set of objects via a set of coordinates for the objects on a limited number of dimensions. An algorithm is presented for fitting the IDIOSCAL model in the least squares sense.…
Descriptors: Algorithms, Estimation (Mathematics), Goodness of Fit, Least Squares Statistics
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Srinivasan, V.; Shocker, Allan D. – Psychometrika, 1973
This paper offers a new methodology for analyzing individual differences in preference judgments with regard to a set of stimuli. (Author)
Descriptors: Algorithms, Goodness of Fit, Models, Multidimensional Scaling
Peer reviewed Peer reviewed
Ten Berge, Jos M. F.; And Others – Psychometrika, 1994
The suggestion that the IDIOSCAL model be fitted by the TUCKALS2 algorithm for three-way components analysis is examined. The claim that resulting coordinate matrices will be identical is supported when the data matrices are semidefinite. Counterexamples for indefinite matrices are also constructed. (SLD)
Descriptors: Algorithms, Correlation, Equations (Mathematics), Goodness of Fit
Peer reviewed Peer reviewed
Johnson, Richard M. – Psychometrika, 1973
A method of nonmetric multidimensional scaling is described which minimizes pairwise departures from monotonicity. (Author)
Descriptors: Algorithms, Calculus, Computer Programs, Data Analysis
Peer reviewed Peer reviewed
Davison, Mark L. – Psychometrika, 1976
Proposes a quadratic programming, least squares solution to Carroll's weighted unfolding model with nonnegativity constraints imposed on weights. It can be used to test various hypotheses about the weighted unfolding model with or without constraints. (RC)
Descriptors: Algorithms, Correlation, Goodness of Fit, Hypothesis Testing
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