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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
Peer reviewed Peer reviewed
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
Peer reviewed Peer reviewed
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
Peer reviewed Peer reviewed
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)
Peer reviewed Peer reviewed
Ichikawa, Masanori – Psychometrika, 1992
Asymptotic distributions of the estimators of communalities are derived for the maximum likelihood method in factor analysis. It is shown that equating the asymptotic standard error of the communality estimate to the unique variance estimate is not correct for the unstandardized case. Monte Carlo simulations illustrate the study. (SLD)
Descriptors: Computer Simulation, Equations (Mathematics), Estimation (Mathematics), Factor Analysis
Peer reviewed Peer reviewed
Bissett, Randall; Schneider, Bruce – Psychometrika, 1991
The algorithm developed by B. A. Schneider (1980) for analysis of paired comparisons of psychological intervals is replaced by one proposed by R. M. Johnson. Monte Carlo simulations of pairwise dissimilarities and pairwise conjoint effects show that Johnson's algorithm can provide good metric recovery. (SLD)
Descriptors: Algorithms, Comparative Analysis, Computer Simulation, Equations (Mathematics)
Peer reviewed Peer reviewed
Raaijmakers, Jeroen G. W.; Pieters, Jo P. M. – Psychometrika, 1987
Functional and structural relationship alternatives to the standard "F"-test for analysis of covariance (ANCOVA) are discussed for cases when the covariate is measured with error. An approximate statistical test based on the functional relationship approach is preferred on the basis of Monte Carlo simulation results. (SLD)
Descriptors: Analysis of Covariance, Computer Simulation, Error of Measurement, Hypothesis Testing
Peer reviewed Peer reviewed
Alsawalmeh, Yousef M.; Feldt, Leonard S. – Psychometrika, 1994
A modification of a test of the equality of nonindependent alpha reliability coefficients is proposed. It avoids the limitation that the product of the number of test parts times the number of subjects be quite large. Monte Carlo studies indicate that this test can be used in comparing interrater reliabilities. (SLD)
Descriptors: Comparative Analysis, Computer Simulation, Equations (Mathematics), Interrater Reliability
Peer reviewed Peer reviewed
Stout, William – Psychometrika, 1987
A procedure--based on item response theory--for testing the hypothesis of unidimensionality of the latent space is proposed. Use of the procedure is supported by an asymptotic theory and a Monte Carlo simulation study. The procedure tests for unidimensionality in test construction and/or compares two tests. (SLD)
Descriptors: College Entrance Examinations, Computer Simulation, Equations (Mathematics), Hypothesis Testing
Peer reviewed Peer reviewed
Woodruff, David J.; Feldt, Leonard S. – Psychometrika, 1986
This paper presents 11 statistical procedures which test the equality of m coefficient alphas when the sample alpha coefficients are dependent. Several of the procedures are derived in detail, and numerical examples are given for two. (Author/LMO)
Descriptors: Analysis of Covariance, Analysis of Variance, Computer Simulation, Hypothesis Testing