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Liu, Yang; Yang, Ji Seung – Journal of Educational and Behavioral Statistics, 2018
The uncertainty arising from item parameter estimation is often not negligible and must be accounted for when calculating latent variable (LV) scores in item response theory (IRT). It is particularly so when the calibration sample size is limited and/or the calibration IRT model is complex. In the current work, we treat two-stage IRT scoring as a…
Descriptors: Intervals, Scores, Item Response Theory, Bayesian Statistics
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
Kaplan, David; Su, Dan – Journal of Educational and Behavioral Statistics, 2016
This article presents findings on the consequences of matrix sampling of context questionnaires for the generation of plausible values in large-scale assessments. Three studies are conducted. Study 1 uses data from PISA 2012 to examine several different forms of missing data imputation within the chained equations framework: predictive mean…
Descriptors: Sampling, Questionnaires, Measurement, International Assessment
Zwick, Rebecca – ETS Research Report Series, 2012
Differential item functioning (DIF) analysis is a key component in the evaluation of the fairness and validity of educational tests. The goal of this project was to review the status of ETS DIF analysis procedures, focusing on three aspects: (a) the nature and stringency of the statistical rules used to flag items, (b) the minimum sample size…
Descriptors: Test Bias, Sample Size, Bayesian Statistics, Evaluation Methods
Cepeda-Cuervo, Edilberto; Núñez-Antón, Vicente – Journal of Educational and Behavioral Statistics, 2013
In this article, a proposed Bayesian extension of the generalized beta spatial regression models is applied to the analysis of the quality of education in Colombia. We briefly revise the beta distribution and describe the joint modeling approach for the mean and dispersion parameters in the spatial regression models' setting. Finally, we motivate…
Descriptors: Regression (Statistics), Foreign Countries, Educational Quality, Educational Research
Lavine, Michael – 1987
A specific application of a general paradigm described by R. D. Cook (1986) and R. McCulloch (1985) in assessing local influence is given. Snow geese flock size is estimated as "X" by an observer and "Y" by a photograph. "Y" is believed to be the true flock size. The problem is to obtain true flock size "Z"…
Descriptors: Bayesian Statistics, Equations (Mathematics), Predictive Measurement, Sample Size
Peer reviewedRaudenbush, Stephen W. – Journal of Educational Statistics, 1988
Estimation theory in educational statistics and the application of hierarchical linear models are reviewed. Observations within each group vary as a function of microparameters. Microparameters vary across the population of groups as a function of macroparameters. Bayes and empirical Bayes viewpoints review examples with two levels of hierarchy.…
Descriptors: Bayesian Statistics, Educational Research, Equations (Mathematics), Estimation (Mathematics)
Peer reviewedCooil, Bruce; Rust, Roland T. – Psychometrika, 1995
A proportional reduction in loss (PRL) measure for reliability of categorical data is explored for the situation in which each of "N" judges assigns a subject to one of "K" categories. Calculating a lower bound for reliability under more general conditions than had been proposed is demonstrated. (SLD)
Descriptors: Bayesian Statistics, Classification, Equations (Mathematics), Estimation (Mathematics)
Peer reviewedTsutakawa, Robert K.; Soltys, Michael J. – Journal of Educational Statistics, 1988
An approximation procedure is proposed for the posterior means and standard deviation of the ability parameter in an item response model. The method is illustrated for the two-parameter logistic model using data from a 39-item American College Testing mathematics test. The effect of sample size is considered. (SLD)
Descriptors: Ability, Academic Ability, Bayesian Statistics, Equations (Mathematics)

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