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Chuang, David T.; And Others – Journal of Educational Statistics, 1981
Approaches to the determination of cut-scores have used threshold, normal ogive, linear and discrete utility functions. These approaches are examined by investigating conditions on the posterior, likelihood and utility functions required for setting cut-scores in a Bayesian approach. (Author/JKS)
Descriptors: Bayesian Statistics, Criterion Referenced Tests, Cutting Scores, Decision Making
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Morrison, Donald G.; Brockway, George – Psychometrika, 1979
A modified beta binomial model is presented for use in analyzing random guessing multiple choice tests and taste tests. Detection probabilities for each item are distributed beta across the population subjects. Properties for the observable distribution of correct responses are derived. Two concepts of true score estimates are presented.…
Descriptors: Bayesian Statistics, Guessing (Tests), Mathematical Models, Multiple Choice Tests
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Brunk, H. D. – Psychometrika, 1981
Bayesian techniques are adapted to the estimation of stimulus-response curves. Illustrative examples deal with estimation of person characteristic curves and item characteristic curves in the context of mental testing, and with estimation of a stimulus-response curve using data from a psychophysical experiment. (Author/JKS)
Descriptors: Bayesian Statistics, Item Analysis, Latent Trait Theory, Least Squares Statistics
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Smith, Jeffrey K. – Educational and Psychological Measurement, 1980
Weber contends that the use of Rasch analysis, principal components analysis, and classical test analysis shows that an instrument designed to measure a "bilevel dimensionality" in probability achievement measures a single latent trait. That interpretation and the use of Rasch and classical analysis to establish unidimensionality are…
Descriptors: Academic Achievement, Bayesian Statistics, Cognitive Processes, Item Analysis
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de Campos, Luis M.; Fernandez-Luna, Juan M.; Huete, Juan F. – Journal of the American Society for Information Science and Technology, 2003
Discussion of relevance feedback in information retrieval focuses on a proposal for the Bayesian Network Retrieval Model. Bases the proposal on the propagation of partial evidences in the Bayesian network, representing new information obtained from the user's relevance judgments to compute the posterior relevance probabilities of the documents…
Descriptors: Bayesian Statistics, Feedback, Information Retrieval, Mathematical Formulas
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Song, Xin-Yuan; Lee, Sik-Yum – Psychometrika, 2002
Developed a Bayesian approach for structural equation models with ignorable missing continuous and polytomous data that obtains joint Bayesian estimates of thresholds, structural parameters, and latent factor scores simultaneously. Illustrated the approach through analysis of a real data set of 20 patterns of condom use in the Philippines. (SLD)
Descriptors: Bayesian Statistics, Behavior Patterns, Condoms, Equations (Mathematics)
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Skaggs, Gary; Stevenson, Jose – Applied Psychological Measurement, 1989
Pseudo-Bayesian and joint maximum likelihood procedures were compared for their ability to estimate item parameters for item response theory's (IRT's) three-parameter logistic model. Item responses were generated for sample sizes of 2,000 and 500; test lengths of 35 and 15; and examinees of high, medium, and low ability. (TJH)
Descriptors: Bayesian Statistics, Comparative Analysis, Computer Software, Estimation (Mathematics)
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Anderson, John R. – Psychological Review, 1991
A rational model of human categorization behavior is presented that assumes that categorization reflects the derivation of optimal estimates of the probability of unseen features of objects. A case is made that categorization behavior can be predicted from the structure of the environment. (SLD)
Descriptors: Adjustment (to Environment), Bayesian Statistics, Behavior Patterns, Classification
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Bockenholt, Ulf – Psychometrika, 1993
A flexible class of stochastic mixture models is introduced and illustrated for analysis and interpretation of individual differences in recurrent choice and other types of count data. These models are derived by specifying elements of the choice process at the individual level. An easy-to-implement algorithm is presented for parameter estimation.…
Descriptors: Bayesian Statistics, Decision Making, Equations (Mathematics), Estimation (Mathematics)
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Viana, Marlos A. G. – Journal of Educational Statistics, 1993
Use of linear combinations of Fisher's "z" transformations as a combined test for the common correlation parameter based on "k" independent sample correlations has been previously studied. This article considers additional "z" additive properties and methods of combining independent studies when planning the number of…
Descriptors: Bayesian Statistics, Correlation, Equations (Mathematics), Evaluation Criteria
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Wang, Tianyou; Vispoel, Walter P. – Journal of Educational Measurement, 1998
Used simulations of computerized adaptive tests to evaluate results yielded by four commonly used ability estimation methods: maximum likelihood estimation (MLE) and three Bayesian approaches. Results show clear distinctions between MLE and Bayesian methods. (SLD)
Descriptors: Ability, Adaptive Testing, Bayesian Statistics, Computer Assisted Testing
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Tsiouris, John; Mann, Rachel; Patti, Paul; Sturmey, Peter – Journal of Intellectual and Developmental Disability, 2004
Clinicians need to know the likelihood of a condition given a positive or negative diagnostic test. In this study a Bayesian analysis of the Clinical Behavior Checklist for Persons with Intellectual Disabilities (CBCPID) to predict depression in people with intellectual disability was conducted. The CBCPID was administered to 92 adults with…
Descriptors: Bayesian Statistics, Clinical Diagnosis, Predictor Variables, Depression (Psychology)
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Ansari, Asim; Iyengar, Raghuram – Psychometrika, 2006
We develop semiparametric Bayesian Thurstonian models for analyzing repeated choice decisions involving multinomial, multivariate binary or multivariate ordinal data. Our modeling framework has multiple components that together yield considerable flexibility in modeling preference utilities, cross-sectional heterogeneity and parameter-driven…
Descriptors: Markov Processes, Monte Carlo Methods, Computation, Bayesian Statistics
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Torralba, Antonio; Oliva, Aude; Castelhano, Monica S.; Henderson, John M. – Psychological Review, 2006
Many experiments have shown that the human visual system makes extensive use of contextual information for facilitating object search in natural scenes. However, the question of how to formally model contextual influences is still open. On the basis of a Bayesian framework, the authors present an original approach of attentional guidance by global…
Descriptors: Guidance, Eye Movements, Attention, Role
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Sinharay, Sandip; Johnson, Matthew S.; Stern, Hal S. – Applied Psychological Measurement, 2006
Model checking in item response theory (IRT) is an underdeveloped area. There is no universally accepted tool for checking IRT models. The posterior predictive model-checking method is a popular Bayesian model-checking tool because it has intuitive appeal, is simple to apply, has a strong theoretical basis, and can provide graphical or numerical…
Descriptors: Predictive Measurement, Item Response Theory, Bayesian Statistics, Models
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