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Mislevy, Robert J. | 2 |
Akaike, Hirotugu | 1 |
Almond, Russell G. | 1 |
Arminger, Gerhard | 1 |
Levy, Roy | 1 |
Lind, Douglas A. | 1 |
Muthen, Bengt O. | 1 |
Segawa, Eisuke | 1 |
Tsutakawa, Robert K. | 1 |
Williamson, David M. | 1 |
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Reports - Descriptive | 7 |
Journal Articles | 3 |
Speeches/Meeting Papers | 3 |
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Arminger, Gerhard; Muthen, Bengt O. – Psychometrika, 1998
Nonlinear latent variable models are specified that include quadratic forms and interactions of latent regressor variable as special cases. To estimate the parameters, the models are put in a Bayesian framework with conjugate priors for the parameters. The proposed estimation methods are illustrated by two simulation studies. (SLD)
Descriptors: Algorithms, Bayesian Statistics, Estimation (Mathematics), Mathematical Models
Williamson, David M.; Mislevy, Robert J.; Almond, Russell G. – 2001
This study investigated statistical methods for identifying errors in Bayesian networks (BN) with latent variables, as found in intelligent cognitive assessments. BN, commonly used in artificial intelligence systems, are promising mechanisms for scoring constructed-response examinations. The success of an intelligent assessment or tutoring system…
Descriptors: Artificial Intelligence, Bayesian Statistics, Cognitive Tests, Mathematical Models

Akaike, Hirotugu – Psychometrika, 1987
The Akaike Information Criterion (AIC) was introduced to extend the method of maximum likelihood to the multimodel situation. Use of the AIC in factor analysis is interesting when it is viewed as the choice of a Bayesian model; thus, wider applications of AIC are possible. (Author/GDC)
Descriptors: Bayesian Statistics, Factor Analysis, Mathematical Models, Maximum Likelihood Statistics
Levy, Roy; Mislevy, Robert J. – 2003
This paper aims to describe a Bayesian approach to modeling and estimating cognitive models both in terms of statistical machinery and actual instrument development. Such a method taps the knowledge of experts to provide initial estimates for the probabilistic relationships among the variables in a multivariate latent variable model and refines…
Descriptors: Bayesian Statistics, Cognitive Processes, Markov Processes, Mathematical Models
Lind, Douglas A. – 1979
The use of subjective probability as a theoretical model for enrollment forecasting is proposed, and the results of an application of subjective probability to enrollment forecasting at the University of Toledo are reported. Subjective probability can be used as an enrollment forecasting technique for both headcount and full-time equivalent using…
Descriptors: Bayesian Statistics, Conference Reports, Enrollment Projections, Higher Education
Segawa, Eisuke – Journal of Educational and Behavioral Statistics, 2005
Multi-indicator growth models were formulated as special three-level hierarchical generalized linear models to analyze growth of a trait latent variable measured by ordinal items. Items are nested within a time-point, and time-points are nested within subject. These models are special because they include factor analytic structure. This model can…
Descriptors: Bayesian Statistics, Mathematical Models, Factor Analysis, Computer Simulation
Tsutakawa, Robert K. – 1984
This report describes new statistical procedures for item response analysis using estimation of item response curves used in mental testing with ability parameters treated as a random sample. Modern computer technology and the EM algorithm make this solution possible. The research focused on the theoretical formulation and solution of maximum…
Descriptors: Ability, Bayesian Statistics, Estimation (Mathematics), Item Sampling