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Christine E. DeMars; Paulius Satkus – Educational and Psychological Measurement, 2024
Marginal maximum likelihood, a common estimation method for item response theory models, is not inherently a Bayesian procedure. However, due to estimation difficulties, Bayesian priors are often applied to the likelihood when estimating 3PL models, especially with small samples. Little focus has been placed on choosing the priors for marginal…
Descriptors: Item Response Theory, Statistical Distributions, Error of Measurement, Bayesian Statistics
Karadavut, Tugba – International Journal of Assessment Tools in Education, 2019
Item Response Theory (IRT) models traditionally assume a normal distribution for ability. Although normality is often a reasonable assumption for ability, it is rarely met for observed scores in educational and psychological measurement. Assumptions regarding ability distribution were previously shown to have an effect on IRT parameter estimation.…
Descriptors: Item Response Theory, Computation, Bayesian Statistics, Ability
Qiao, Xin; Jiao, Hong; He, Qiwei – Journal of Educational Measurement, 2023
Multiple group modeling is one of the methods to address the measurement noninvariance issue. Traditional studies on multiple group modeling have mainly focused on item responses. In computer-based assessments, joint modeling of response times and action counts with item responses helps estimate the latent speed and action levels in addition to…
Descriptors: Multivariate Analysis, Models, Item Response Theory, Statistical Distributions
Ames, Allison J. – Measurement: Interdisciplinary Research and Perspectives, 2018
Bayesian item response theory (IRT) modeling stages include (a) specifying the IRT likelihood model, (b) specifying the parameter prior distributions, (c) obtaining the posterior distribution, and (d) making appropriate inferences. The latter stage, and the focus of this research, includes model criticism. Choice of priors with the posterior…
Descriptors: Bayesian Statistics, Item Response Theory, Statistical Inference, Prediction
Kim, Seohyun; Lu, Zhenqiu; Cohen, Allan S. – Measurement: Interdisciplinary Research and Perspectives, 2018
Bayesian algorithms have been used successfully in the social and behavioral sciences to analyze dichotomous data particularly with complex structural equation models. In this study, we investigate the use of the Polya-Gamma data augmentation method with Gibbs sampling to improve estimation of structural equation models with dichotomous variables.…
Descriptors: Bayesian Statistics, Structural Equation Models, Computation, Social Science Research
Silva, R. M.; Guan, Y.; Swartz, T. B. – Journal on Efficiency and Responsibility in Education and Science, 2017
This paper attempts to bridge the gap between classical test theory and item response theory. It is demonstrated that the familiar and popular statistics used in classical test theory can be translated into a Bayesian framework where all of the advantages of the Bayesian paradigm can be realized. In particular, prior opinion can be introduced and…
Descriptors: Item Response Theory, Bayesian Statistics, Test Construction, Markov Processes
Yildiz, Mustafa – ProQuest LLC, 2017
Student misconceptions have been studied for decades from a curricular/instructional perspective and from the assessment/test level perspective. Numerous misconception assessment tools have been developed in order to measure students' misconceptions relative to the correct content. Often, these tools are used to make a variety of educational…
Descriptors: Misconceptions, Students, Item Response Theory, Models
Culpepper, Steven Andrew; Park, Trevor – Journal of Educational and Behavioral Statistics, 2017
A latent multivariate regression model is developed that employs a generalized asymmetric Laplace (GAL) prior distribution for regression coefficients. The model is designed for high-dimensional applications where an approximate sparsity condition is satisfied, such that many regression coefficients are near zero after accounting for all the model…
Descriptors: Bayesian Statistics, Multivariate Analysis, Item Response Theory, Regression (Statistics)
Kim, Sooyeon; Moses, Tim; Yoo, Hanwook Henry – ETS Research Report Series, 2015
The purpose of this inquiry was to investigate the effectiveness of item response theory (IRT) proficiency estimators in terms of estimation bias and error under multistage testing (MST). We chose a 2-stage MST design in which 1 adaptation to the examinees' ability levels takes place. It includes 4 modules (1 at Stage 1, 3 at Stage 2) and 3 paths…
Descriptors: Item Response Theory, Computation, Statistical Bias, Error of Measurement
Finch, Holmes; Edwards, Julianne M. – Educational and Psychological Measurement, 2016
Standard approaches for estimating item response theory (IRT) model parameters generally work under the assumption that the latent trait being measured by a set of items follows the normal distribution. Estimation of IRT parameters in the presence of nonnormal latent traits has been shown to generate biased person and item parameter estimates. A…
Descriptors: Item Response Theory, Computation, Nonparametric Statistics, Bayesian Statistics
Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2015
Person-fit assessment may help the researcher to obtain additional information regarding the answering behavior of persons. Although several researchers examined person fit, there is a lack of research on person-fit assessment for mixed-format tests. In this article, the lz statistic and the ?2 statistic, both of which have been used for tests…
Descriptors: Test Format, Goodness of Fit, Item Response Theory, Bayesian Statistics
Skaggs, Gary; Wilkins, Jesse L. M.; Hein, Serge F. – International Journal of Testing, 2016
The purpose of this study was to explore the degree of grain size of the attributes and the sample sizes that can support accurate parameter recovery with the General Diagnostic Model (GDM) for a large-scale international assessment. In this resampling study, bootstrap samples were obtained from the 2003 Grade 8 TIMSS in Mathematics at varying…
Descriptors: Achievement Tests, Foreign Countries, Elementary Secondary Education, Science Achievement
MacDonald, George T. – ProQuest LLC, 2014
A simulation study was conducted to explore the performance of the linear logistic test model (LLTM) when the relationships between items and cognitive components were misspecified. Factors manipulated included percent of misspecification (0%, 1%, 5%, 10%, and 15%), form of misspecification (under-specification, balanced misspecification, and…
Descriptors: Simulation, Item Response Theory, Models, Test Items
Seo, Dong Gi; Weiss, David J. – Educational and Psychological Measurement, 2013
The usefulness of the l[subscript z] person-fit index was investigated with achievement test data from 20 exams given to more than 3,200 college students. Results for three methods of estimating ? showed that the distributions of l[subscript z] were not consistent with its theoretical distribution, resulting in general overfit to the item response…
Descriptors: Achievement Tests, College Students, Goodness of Fit, Item Response Theory

Harwell, Michael R.; Janosky, Janine E. – Applied Psychological Measurement, 1991
Investigates the BILOG computer program's ability to recover known item parameters for different numbers of items, examinees, and variances of the prior distributions of discrimination parameters for the two-parameter logistic item-response theory model. For samples of at least 250 examinees and 15 items, simulation results support using BILOG.…
Descriptors: Bayesian Statistics, Computer Simulation, Estimation (Mathematics), Item Response Theory
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