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San Martin, Ernesto; Jara, Alejandro; Rolin, Jean-Marie; Mouchart, Michel – Psychometrika, 2011
We study the identification and consistency of Bayesian semiparametric IRT-type models, where the uncertainty on the abilities' distribution is modeled using a prior distribution on the space of probability measures. We show that for the semiparametric Rasch Poisson counts model, simple restrictions ensure the identification of a general…
Descriptors: Identification, Probability, Item Response Theory, Bayesian Statistics
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Miyazaki, Kei; Hoshino, Takahiro – Psychometrika, 2009
In Item Response Theory (IRT), item characteristic curves (ICCs) are illustrated through logistic models or normal ogive models, and the probability that examinees give the correct answer is usually a monotonically increasing function of their ability parameters. However, since only limited patterns of shapes can be obtained from logistic models…
Descriptors: Nonverbal Communication, Probability, Item Response Theory, Bayesian Statistics
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Iliopoulos, G.; Kateri, M.; Ntzoufras, I. – Psychometrika, 2009
Association models constitute an attractive alternative to the usual log-linear models for modeling the dependence between classification variables. They impose special structure on the underlying association by assigning scores on the levels of each classification variable, which can be fixed or parametric. Under the general row-column (RC)…
Descriptors: Markov Processes, Classification, Bayesian Statistics, Probability
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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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Duncan, George T. – Psychometrika, 1978
Statistical procedures based on Bayesian estimation for obtaining estimates of a propensity (which would include estimates of proportions or relative frequencies) are described for the special case where the observer can only note whether the propensity exceeds or does not exceed a constant between 0 and 1. (JKS)
Descriptors: Bayesian Statistics, Decision Making, Hypothesis Testing, Probability
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Fornell, Claes; Rust, Roland T. – Psychometrika, 1989
A Bayesian approach to the testing of competing covariance structures is developed. Approximate posterior probabilities are easily obtained from the chi square values and other known constants. The approach is illustrated using an example that demonstrates how the prior probabilities can alter results concerning the preferred model specification.…
Descriptors: Bayesian Statistics, Chi Square, Comparative Analysis, Mathematical Models
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Camilli, Gregory – Psychometrika, 1995
This paper demonstrates that two major tests for two-by-two tables, Fisher's exact and Pearson's chi-square tests, are highly related from a Bayesian perspective. A formal similarity is demonstrated in small samples, and reasons for the relationship are discussed. (SLD)
Descriptors: Bayesian Statistics, Chi Square, Equations (Mathematics), Probability
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Kearns, Jack; Meredith, William – Psychometrika, 1975
Examines the question of how large a sample must be in order to produce empirical Bayes estimates which are preferable to other commonly used estimates, such as proportion correct observed score. (Author/RC)
Descriptors: Bayesian Statistics, Item Analysis, Probability, Sampling
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Lewis, Charles; And Others – Psychometrika, 1975
A Bayesian Model II approach to the estimation of proportions in m groups is extended to obtain posterior marginal distributions for the proportions. The approach is extended to allow greater use of prior information than previously and the specification of this prior information is discussed. (Author/RC)
Descriptors: Bayesian Statistics, Data Analysis, Individualized Instruction, Models
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Wilcox, Rand R. – Psychometrika, 1978
Several Bayesian approaches to the simultaneous estimation of the means of k binomial populations are discussed. This has particular applicability to criterion-referenced or mastery testing. (Author/JKS)
Descriptors: Bayesian Statistics, Criterion Referenced Tests, Mastery Tests, Probability
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Fligner, Michael A.; Verducci, Joseph S. – Psychometrika, 1990
The concept of consensus ordering is defined, and formulas for exact and approximate posterior probabilities for consensus ordering are developed under the assumption of a generalized Mallows' model with a diffuse conjugate prior. These methods are applied to a data set concerning 98 college students. (SLD)
Descriptors: Bayesian Statistics, College Students, Equations (Mathematics), Estimation (Mathematics)
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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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Chang, Hua-Hua; Stout, William – Psychometrika, 1993
The asymptotic posterior normality of latent variable distributions is established under very general and appropriate hypotheses, providing a probabilistic basis for assessing ability estimation/prediction accuracy in the long test case, as well as a first step in making the Dutch Identity conjecture rigorous. (SLD)
Descriptors: Ability, Bayesian Statistics, Equations (Mathematics), Estimation (Mathematics)
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Mislevy, Robert J. – Psychometrika, 1994
Educational assessment concerns inference about student knowledge, skills, and accomplishments. Test theory has evolved in part to address questions of weight, coverage, and import of data. Resulting concepts and techniques can be viewed as applications of more general principles for inference in the presence of uncertainty. (SLD)
Descriptors: Bayesian Statistics, Cognitive Psychology, Educational Assessment, Inferences