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Kelderman, Henk – Psychometrika, 1992
Describes algorithms used in the computer program LOGIMO for obtaining maximum likelihood estimates of the parameters in loglinear models. These algorithms are also useful for the analysis of loglinear item-response theory models. Presents modified versions of the iterative proportional fitting and Newton-Raphson algorithms. Simulated data…
Descriptors: Algorithms, Computer Simulation, Equations (Mathematics), Estimation (Mathematics)
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Macready, George B.; Dayton, C. Mitchell – Psychometrika, 1992
An adaptive testing algorithm is presented based on an alternative modeling framework, and its effectiveness is investigated in a simulation based on real data. The algorithm uses a latent class modeling framework in which assessed latent attributes are assumed to be categorical variables. (SLD)
Descriptors: Adaptive Testing, Algorithms, Bayesian Statistics, Classification
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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)
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Levine, Michael V.; Drasgow, Fritz – Psychometrika, 1988
Some examinees' test-taking behavior may be so idiosyncratic that their test scores are not comparable to those of more typical examinees. A new theoretical approach to appropriateness measurement is proposed that specifies a likelihood ratio test and an efficient computer algorithm for computing the test statistic. (TJH)
Descriptors: Algorithms, Computer Simulation, Latent Trait Theory, Maximum Likelihood Statistics
Peer reviewed Peer reviewed
Bockenholt, Ulf; Bockenholt, Ingo – Psychometrika, 1991
A reparameterization of a latent class model is presented to classify and scale nomial and ordered categorical choice data simultaneously. The model extension represents a nonhomogeneous population as a mixture of homogeneous subpopulations. Simulated data and data from a magazine preference survey of 347 college students illustrate the model.…
Descriptors: Algorithms, Classification, College Students, Computer Simulation
Peer reviewed Peer reviewed
Kiiveri, H. T. – Psychometrika, 1987
Covariance structures associated with linear structural equation models are discussed. Algorithms for computing maximum likelihood estimates (namely, the EM algorithm) are reviewed. An example of using likelihood ratio tests based on complete and incomplete data to improve the fit of a model is given. (SLD)
Descriptors: Algorithms, Analysis of Covariance, Computer Simulation, Equations (Mathematics)
Peer reviewed Peer reviewed
Liou, Michelle; Chang, Chih-Hsin – Psychometrika, 1992
An extension is proposed for the network algorithm introduced by C.R. Mehta and N.R. Patel to construct exact tail probabilities for testing the general hypothesis that item responses are distributed according to the Rasch model. A simulation study indicates the efficiency of the algorithm. (SLD)
Descriptors: Algorithms, Computer Simulation, Difficulty Level, Equations (Mathematics)
Peer reviewed Peer reviewed
Longford, N. T.; Muthen, B. O. – Psychometrika, 1992
A two-level model for factor analysis is defined, and formulas for a scoring algorithm for this model are derived. A simple noniterative method based on decomposition of total sums of the squares and cross-products is discussed and illustrated with simulated data and data from the Second International Mathematics Study. (SLD)
Descriptors: Algorithms, Cluster Analysis, Computer Simulation, Equations (Mathematics)