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Luo, Yong; Jiao, Hong – Educational and Psychological Measurement, 2018
Stan is a new Bayesian statistical software program that implements the powerful and efficient Hamiltonian Monte Carlo (HMC) algorithm. To date there is not a source that systematically provides Stan code for various item response theory (IRT) models. This article provides Stan code for three representative IRT models, including the…
Descriptors: Bayesian Statistics, Item Response Theory, Probability, Computer Software
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Wilcox, Rand R. – Educational and Psychological Measurement, 2006
Consider the nonparametric regression model Y = m(X)+ [tau](X)[epsilon], where X and [epsilon] are independent random variables, [epsilon] has a median of zero and variance [sigma][squared], [tau] is some unknown function used to model heteroscedasticity, and m(X) is an unknown function reflecting some conditional measure of location associated…
Descriptors: Nonparametric Statistics, Mathematical Models, Regression (Statistics), Probability
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Zimmerman, Donald W. – Educational and Psychological Measurement, 1976
Using the concepts of conditional probability, conditional expectation, and conditional independence, the main results of the classical test theory model can be derived in a very few steps with minimal assumptions. The present effort explores the possibility that present classical test theories can be further condensed. (Author/RC)
Descriptors: Career Development, Correlation, Mathematical Models, Measurement
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Lienert, G. A.; Krauth, J. – Educational and Psychological Measurement, 1975
Configural frequency analysis (CFA), a new method for identifying types, is illustrated numerically. Relations to latent class analysis and to factor analysis are discussed. It is suggested to use CFA as a type-defining method instead of factor analysis if the variables are linked not only by first but also by higher-order associations. (RC)
Descriptors: Classification, Factor Analysis, Hypothesis Testing, Mathematical Models
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Dagenais, Denyse L. – Educational and Psychological Measurement, 1984
After a review of the disadvantages of linear models for estimating the probability of academic success from previous school records and admission test results, the use of a probit model is proposed. The model is illustrated with admissions data from the Ecole des Hautes Etudes Commerciales in Montreal. (Author/BW)
Descriptors: Admission (School), Admission Criteria, Dropout Rate, Estimation (Mathematics)
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Wilcox, Rand R. – Educational and Psychological Measurement, 1981
A formal framework is presented for determining which of the distractors of multiple-choice test items has a small probability of being chosen by a typical examinee. The framework is based on a procedure similar to an indifference zone formulation of a ranking and election problem. (Author/BW)
Descriptors: Mathematical Models, Multiple Choice Tests, Probability, Test Items
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Bergman, Lars R.; El-Khouri, Bassam – Educational and Psychological Measurement, 1987
A program named EXACON is presented which performs exact cellwise analyses of two-way contingency tables. One-tailed probabilities are computed for the observed frequency of each cell according to two different models. Even though exact probabilities are computed, EXACON does not demand much computer time even for fairly large samples. (Author/LMO)
Descriptors: Computer Software Reviews, Input Output, Mathematical Models, Minicomputers
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Davenport, Ernest C., Jr.; El-Sanhurry, Nader A. – Educational and Psychological Measurement, 1991
The phimax adjustment to phi (Pearson's product moment correlation applied to binary data) is explored. Phi/phimax is shown to be a measure of relationship apart from its affiliation with phi. The relations between phi/phimax and kappa and limitations of phi/phimax are discussed. (SLD)
Descriptors: Correlation, Equations (Mathematics), Mathematical Models, Probability
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Wilcox, Rand R. – Educational and Psychological Measurement, 1979
Wilcox has described three probability models which characterize a single test item in terms of a population of examinees (ED 156 718). This note indicates indicates that similar models can be derived which characterize a single examinee in terms of an item domain. A numerical illustration is given. (Author/JKS)
Descriptors: Achievement Tests, Item Analysis, Mathematical Models, Probability
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Lissitz, Robert W.; Halperin, Silas – Educational and Psychological Measurement, 1971
Descriptors: Behavioral Science Research, Computer Programs, Hypothesis Testing, Mathematical Models