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Giada Spaccapanico Proietti; Mariagiulia Matteucci; Stefania Mignani; Bernard P. Veldkamp – Journal of Educational and Behavioral Statistics, 2024
Classical automated test assembly (ATA) methods assume fixed and known coefficients for the constraints and the objective function. This hypothesis is not true for the estimates of item response theory parameters, which are crucial elements in test assembly classical models. To account for uncertainty in ATA, we propose a chance-constrained…
Descriptors: Automation, Computer Assisted Testing, Ambiguity (Context), Item Response Theory
Monroe, Scott – Journal of Educational and Behavioral Statistics, 2021
This research proposes a new statistic for testing latent variable distribution fit for unidimensional item response theory (IRT) models. If the typical assumption of normality is violated, then item parameter estimates will be biased, and dependent quantities such as IRT score estimates will be adversely affected. The proposed statistic compares…
Descriptors: Item Response Theory, Simulation, Scores, Comparative Analysis
Martin, Michael O.; Mullis, Ina V. S. – Journal of Educational and Behavioral Statistics, 2019
International large-scale assessments of student achievement such as International Association for the Evaluation of Educational Achievement's Trends in International Mathematics and Science Study (TIMSS) and Progress in International Reading Literacy Study and Organization for Economic Cooperation and Development's Program for International…
Descriptors: Achievement Tests, International Assessment, Mathematics Tests, Science Achievement
Camilli, Gregory; Fox, Jean-Paul – Journal of Educational and Behavioral Statistics, 2015
An aggregation strategy is proposed to potentially address practical limitation related to computing resources for two-level multidimensional item response theory (MIRT) models with large data sets. The aggregate model is derived by integration of the normal ogive model, and an adaptation of the stochastic approximation expectation maximization…
Descriptors: Factor Analysis, Item Response Theory, Grade 4, Simulation
Rijmen, Frank; Jeon, Minjeong; von Davier, Matthias; Rabe-Hesketh, Sophia – Journal of Educational and Behavioral Statistics, 2014
Second-order item response theory models have been used for assessments consisting of several domains, such as content areas. We extend the second-order model to a third-order model for assessments that include subdomains nested in domains. Using a graphical model framework, it is shown how the model does not suffer from the curse of…
Descriptors: Item Response Theory, Models, Educational Assessment, Computation
Bennink, Margot; Croon, Marcel A.; Keuning, Jos; Vermunt, Jeroen K. – Journal of Educational and Behavioral Statistics, 2014
In educational measurement, responses of students on items are used not only to measure the ability of students, but also to evaluate and compare the performance of schools. Analysis should ideally account for the multilevel structure of the data, and school-level processes not related to ability, such as working climate and administration…
Descriptors: Academic Ability, Educational Assessment, Educational Testing, Test Bias