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Liao, Xiangyi; Bolt, Daniel M. – Journal of Educational and Behavioral Statistics, 2021
Four-parameter models have received increasing psychometric attention in recent years, as a reduced upper asymptote for item characteristic curves can be appealing for measurement applications such as adaptive testing and person-fit assessment. However, applications can be challenging due to the large number of parameters in the model. In this…
Descriptors: Test Items, Models, Mathematics Tests, Item Response Theory
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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
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Loeb, Susanna; Christian, Michael S.; Hough, Heather; Meyer, Robert H.; Rice, Andrew B.; West, Martin R. – Journal of Educational and Behavioral Statistics, 2019
Measures of school-level growth in student outcomes are common tools for assessing the impacts of schools. The vast majority of these measures use standardized tests as the outcome of interest, even though emerging evidence demonstrates the importance of social-emotional learning (SEL). In this article, we present results from using the first…
Descriptors: Social Development, Emotional Development, Student Surveys, Institutional Characteristics
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Jia, Yue; Stokes, Lynne; Harris, Ian; Wang, Yan – Journal of Educational and Behavioral Statistics, 2011
In this article, we consider estimation of parameters of random effects models from samples collected via complex multistage designs. Incorporation of sampling weights is one way to reduce estimation bias due to unequal probabilities of selection. Several weighting methods have been proposed in the literature for estimating the parameters of…
Descriptors: Sampling, Computation, Statistical Bias, Statistical Analysis
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von Davier, Matthias; Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2010
This article presents an application of a stochastic approximation expectation maximization (EM) algorithm using a Metropolis-Hastings (MH) sampler to estimate the parameters of an item response latent regression model. Latent regression item response models are extensions of item response theory (IRT) to a latent variable model with covariates…
Descriptors: Item Response Theory, Statistical Analysis, Regression (Statistics), Models
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Hong, Guanglei; Raudenbush, Stephen W. – Journal of Educational and Behavioral Statistics, 2008
The authors propose a strategy for studying the effects of time-varying instructional treatments on repeatedly observed student achievement. This approach responds to three challenges: (a) The yearly reallocation of students to classrooms and teachers creates a complex structure of dependence among responses; (b) a child's learning outcome under a…
Descriptors: Elementary School Mathematics, Grade 4, Probability, Teaching Methods