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Molenaar, Ivo W. – Psychometrika, 1998
Explores the robustness of conclusions from a statistical model against variations in model choice with an illustration from G. Box and G. Tiao (1973). Suggests that simultaneous consideration of a class of models for the same data is sometimes superior to analyzing the data under one model and demonstrates advantages to Adaptive Bayesian…
Descriptors: Bayesian Statistics, Data Analysis, Models, Robustness (Statistics)
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Vos, Hans J. – Journal of Educational and Behavioral Statistics, 1999
Formulates optimal sequential rules for mastery testing using an approach derived from Bayesian sequential decision theory to consider both threshold and linear loss structures. Adopts the binomial probability distribution as the psychometric model. Provides an empirical example for concept-learning in medicine. (SLD)
Descriptors: Bayesian Statistics, Equations (Mathematics), Mastery Tests, Probability
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Meulders, Michel; De Boeck, Paul; Van Mechelen, Iven; Gelman, Andrew; Maris, Eric – Journal of Educational and Behavioral Statistics, 2001
Presents a fully Bayesian analysis for the Probability Matrix Decomposition (PMD) model using the Gibbs sampler. Identifies the advantages of this approach and illustrates the approach by applying the PMD model to opinions of respondents from different countries concerning the possibility of contracting AIDS in a specific situation. (SLD)
Descriptors: Bayesian Statistics, Matrices, Probability, Psychometrics
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Johnson, Matthew S.; Sinharay, Sandip – Applied Psychological Measurement, 2005
For complex educational assessments, there is an increasing use of item families, which are groups of related items. Calibration or scoring in an assessment involving item families requires models that can take into account the dependence structure inherent among the items that belong to the same item family. This article extends earlier works in…
Descriptors: National Competency Tests, Markov Processes, Bayesian Statistics
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Lee, Michael D.; Wagenmakers, Eric-Jan – Psychological Review, 2005
D. Trafimow presented an analysis of null hypothesis significance testing (NHST) using Bayes's theorem. Among other points, he concluded that NHST is logically invalid, but that logically valid Bayesian analyses are often not possible. The latter conclusion reflects a fundamental misunderstanding of the nature of Bayesian inference. This view…
Descriptors: Psychology, Statistical Inference, Statistical Significance, Bayesian Statistics
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Lee, Michael D.; Wagenmakers, Eric-Jan – Psychological Review, 2005
This paper comments on the response offered by Trafimow on Lee and Wagenmakers comments on Trafimow's original article. It seems our comment should have made it clear that the objective Bayesian approach we advocate views probabilities neither as relative frequencies nor as belief states, but as degrees of plausibility assigned to propositions in…
Descriptors: Researchers, Probability, Statistical Inference, Bayesian Statistics
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Klein Entink, Rinke H.; Kuhn, Jorg-Tobias; Hornke, Lutz F.; Fox, Jean-Paul – Psychological Methods, 2009
In current psychological research, the analysis of data from computer-based assessments or experiments is often confined to accuracy scores. Response times, although being an important source of additional information, are either neglected or analyzed separately. In this article, a new model is developed that allows the simultaneous analysis of…
Descriptors: Psychological Studies, Monte Carlo Methods, Markov Processes, Educational Assessment
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Brewer, James K. – American Educational Research Journal, 1974
See TM 501 201-3 and EJ 060 883 for related articles. (MLP)
Descriptors: Bayesian Statistics, Hypothesis Testing, Power (Statistics), Statistical Significance
Wood, R. – Programmed Learning and Educational Technology, 1976
Descriptors: Adaptive Testing, Bayesian Statistics, Intelligence Tests, Test Construction
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Pohl, Norval F.; Bruno, Albert V. – Educational and Psychological Measurement, 1976
A computer program for two-group nonparametric discriminant analysis is presented. Based on Bayes' Theorem for probability revision, the statistical rationale for this program uses the calculation of maximum likelihood estimates of group membership. The program compares the Bayesian procedure to the standard Linear Discriminant Function.…
Descriptors: Bayesian Statistics, Computer Programs, Discriminant Analysis, Nonparametric Statistics
Hoyle, W. G. – Information Storage and Retrieval, 1973
A system of automatic indexing based on Baye's theorem is described briefly. (18 references) (Author)
Descriptors: Algorithms, Automatic Indexing, Bayesian Statistics, Classification
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Wolter, David G.; Earl, Robert W. – Psychometrika, 1972
Descriptors: Bayesian Statistics, Learning, Mathematical Models, Probability
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Geisser, Seymour; Kappenman, Russell F. – Psychometrika, 1971
Descriptors: Bayesian Statistics, Mathematics, Probability, Profiles
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Laughlin, James E. – Psychometrika, 1979
This paper details a Bayesian alternative to the use of least squares and equal weighting coefficients in regression. An equal weight prior distribution for the linear regression parameters is described with regard to the conditional normal regression model, and resulting posterior distributions for these parameters are detailed. (Author/CTM)
Descriptors: Bayesian Statistics, Multiple Regression Analysis, Simulation, Statistical Bias
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Lee, Sik-Yum – Psychometrika, 1981
Confirmatory factor analysis is considered from a Bayesian viewpoint, in which prior information concerning parameters is incorporated in the analysis. An interactive algorithm is developed to obtain the Bayesian estimates. A numerical example is presented. (Author/JKS)
Descriptors: Algorithms, Bayesian Statistics, Factor Analysis, Maximum Likelihood Statistics
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