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Bacon, Donald R. – Structural Equation Modeling, 2001
Evaluated the performance of several alternative cluster analytic approaches to initial model specification using population parameter analyses and a Monte Carlo simulation. Of the six cluster approaches evaluated, the one using the correlations of item correlations as a proximity metric and average linking as a clustering algorithm performed the…
Descriptors: Algorithms, Cluster Analysis, Correlation, Mathematical Models
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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)
Peer reviewed Peer reviewed
Cudeck, Robert – Journal of Educational Statistics, 1991
Two algorithms that automatically select subsets of variables (PACE algorithm) and reference variables (Fabin estimators), respectively, used for the noniterative estimators are presented. The PACE algorithm is based on a nonsymmetric matrix sweep operator. A Monte Carlo experiment compares the relative performance of these estimators and others.…
Descriptors: Algorithms, Comparative Analysis, Equations (Mathematics), Estimation (Mathematics)
Peer reviewed Peer reviewed
Schweizer, Karl – Multivariate Behavioral Research, 1991
A mathematical formula is introduced for the effect of integrating data. A method is then derived to eliminate the effect from correlations of variables, including mean composites, thus allowing for a clustering algorithm that requires allocation of variables according to the magnitude of their correlations. Examples illustrate the procedure. (SLD)
Descriptors: Algorithms, Classification, Cluster Analysis, Computer Simulation
Butler, Ronald W. – 1985
The dynamic linear model or Kalman filtering model provides a useful methodology for predicting the past, present, and future states of a dynamic system, such as an object in motion or an economic or social indicator that is changing systematically with time. Recursive likelihood methods for adaptive Kalman filtering and smoothing are developed.…
Descriptors: Algorithms, Estimation (Mathematics), Mathematical Models, Maximum Likelihood Statistics
Peer reviewed Peer reviewed
Reise, Steven P.; Due, Allan M. – Applied Psychological Measurement, 1991
Previous person-fit research is extended through explication of an unexplored model for generating aberrant response patterns. The proposed model is then implemented to investigate the influence of test properties on the aberrancy detection power of a person-fit statistic. Difficulties of aberrancy detection are discussed. (SLD)
Descriptors: Algorithms, Computer Simulation, Item Response Theory, Mathematical Models
Peer reviewed Peer reviewed
Cudeck, Robert; Browne, Michael W. – Psychometrika, 1992
A method is proposed for constructing a population covariance matrix as the sum of a particular model plus a nonstochastic residual matrix, with the stipulation that the model holds with a prespecified lack of fit. The procedure is considered promising for Monte Carlo studies. (SLD)
Descriptors: Algorithms, Equations (Mathematics), Estimation (Mathematics), Factor Analysis