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Skrondal, Anders; Kuha, Jouni – Psychometrika, 2012
The likelihood for generalized linear models with covariate measurement error cannot in general be expressed in closed form, which makes maximum likelihood estimation taxing. A popular alternative is regression calibration which is computationally efficient at the cost of inconsistent estimation. We propose an improved regression calibration…
Descriptors: Computation, Maximum Likelihood Statistics, Error of Measurement, Regression (Statistics)
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

Roskam, Edward E.; Jansen, Paul G. W. – Psychometrika, 1989
A general dichotomous condition is derived for the unidimensional polytomous Rasch model. The robustness of the dichotomous analysis is investigated in a simulation study. The model shows a close relation with the two-parameter Birnbaum model. (TJH)
Descriptors: Computer Simulation, Equations (Mathematics), Latent Trait Theory, Mathematical Models

Muthen, Bengt; And Others – Psychometrika, 1987
A general latent variable model allows for maximum likelihood estimation with missing data. LISREL and LISCOMP programs may be used to carry out this estimation. Simulated data were generated. The proposed Full, Quasi-Likelihood estimator was found to be superior to listwise present quasi-likelihood and pairwise present approaches. (Author/GDC)
Descriptors: Computer Simulation, Computer Software, Factor Analysis, Mathematical Models

Balakrishnan, P. V. (Sunder); And Others – Psychometrika, 1994
A simulation study compares nonhierarchical clustering capabilities of a class of neural networks using Kohonen learning with a K-means clustering procedure. The focus is on the ability of the procedures to recover correctly the known cluster structure in the data. Advantages and disadvantages of the procedures are reviewed. (SLD)
Descriptors: Classification, Cluster Analysis, Comparative Analysis, Computer Simulation

ten Berge, Jos M. F.; Kiers, Henk A. L. – Psychometrika, 1996
Some uniqueness properties are presented for the PARAFAC2 model for covariance matrices, focusing on uniqueness in the rank two case of PARAFAC2. PARAFAC2 is shown to be usually unique with four matrices, but not unique with three unless a certain additional assumption is introduced. (SLD)
Descriptors: Analysis of Covariance, Computer Simulation, Equations (Mathematics), Least Squares Statistics

Yen, Wendy M. – Psychometrika, 1987
Comparisons are made between BILOG version 2.2 and LOGIST 5.0 version 2.5 in estimating the item parameters, traits, item characteristic functions, and test characteristic functions for the three-parameter logistic model. Speed and accuracy are reported for a number of 10, 20, and 40-item tests. (Author/GDC)
Descriptors: Comparative Analysis, Computer Simulation, Computer Software, Item Analysis

Cohen, Ayala – Psychometrika, 1986
This article proposes a method for testing equality of variances which exploits Pitman's idea and the computational power of simulations. Several advantages to this method are illustrated. A Monte Carlo study for several combinations of sample sizes and number of variables is presented. (Author/LMO)
Descriptors: Analysis of Covariance, Computer Simulation, Correlation, Hypothesis Testing

Snijders, Tom A. B. – Psychometrika, 1991
A complete enumeration method and a Monte Carlo method are presented to calculate the probability distribution of arbitrary statistics of adjacency matrices when these matrices have the uniform distribution conditional on given row and column sums, and possibly on a given set of structural zeros. (SLD)
Descriptors: Computer Simulation, Equations (Mathematics), Mathematical Models, Matrices

Critchlow, Douglas E.; Fligner, Michael A. – Psychometrika, 1991
A variety of paired comparison, triple comparison, and ranking experiments are discussed as generalized linear models. All such models can be easily fit by maximum likelihood using the GLIM computer package. Examples are presented for a variety of cases using GLIM. (SLD)
Descriptors: Comparative Analysis, Computer Simulation, Computer Software, Equations (Mathematics)

Mendoza, Jorge L. – Psychometrika, 1993
A Fisher's Z transformation is developed for the corrected correlation for conditions when the criterion data are missing because of selection on the predictor and when the criterion was missing at random, not because of selection. The two Z transformations were evaluated in a computer simulation and found accurate. (SLD)
Descriptors: Computer Simulation, Correlation, Equations (Mathematics), Mathematical Models

Umesh, U. N.; Mishra, Sanjay – Psychometrika, 1990
Major issues related to index-of-fit conjoint analysis were addressed in this simulation study. Goals were to develop goodness-of-fit criteria for conjoint analysis; develop tests to determine the significance of conjoint analysis results; and calculate the power of the test of the null hypothesis of random data distribution. (SLD)
Descriptors: Computer Simulation, Goodness of Fit, Monte Carlo Methods, Power (Statistics)

Klauer, Karl Christoph – Psychometrika, 1991
Smallest exact confidence intervals for the ability parameter of the Rasch model are derived and compared to the traditional asymptotically valid intervals based on Fisher information. Tables of exact confidence intervals, termed Clopper-Pearson intervals, can be drawn up with a computer program developed by K. Klauer. (SLD)
Descriptors: Ability, Computer Simulation, Equations (Mathematics), Item Response Theory

Rosenbaum, Paul R. – Psychometrika, 1987
This paper develops and applies three nonparametric comparisons of the shapes of two item characteristic surfaces: (1) proportional latent odds; (2) uniform relative difficulty; and (3) item sensitivity. A method is presented for comparing the relative shapes of two item characteristic curves in two examinee populations who were administered an…
Descriptors: Comparative Analysis, Computer Simulation, Difficulty Level, Item Analysis

Brady, Henry E. – Psychometrika, 1989
Satisfactory results for interpersonally incomparable ordinal survey responses can be obtained by assuming that rankings are based upon a set of multivariate normal latent variables that satisfy factor or ideal point models of choice. Two statistical methods based upon those assumptions are described and illustrated via simulations. (TJH)
Descriptors: Computer Simulation, Data Analysis, Equations (Mathematics), Estimation (Mathematics)