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Reardon, Sean F.; Shear, Benjamin R.; Castellano, Katherine E.; Ho, Andrew D. – Journal of Educational and Behavioral Statistics, 2017
Test score distributions of schools or demographic groups are often summarized by frequencies of students scoring in a small number of ordered proficiency categories. We show that heteroskedastic ordered probit (HETOP) models can be used to estimate means and standard deviations of multiple groups' test score distributions from such data. Because…
Descriptors: Scores, Statistical Analysis, Models, Computation
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Ramsay, James O.; Wiberg, Marie – Journal of Educational and Behavioral Statistics, 2017
This article promotes the use of modern test theory in testing situations where sum scores for binary responses are now used. It directly compares the efficiencies and biases of classical and modern test analyses and finds an improvement in the root mean squared error of ability estimates of about 5% for two designed multiple-choice tests and…
Descriptors: Scoring, Test Theory, Computation, Maximum Likelihood Statistics
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Bohrnstedt, G.; Kitmitto, S.; Ogut, B.; Sherman, D.; Chan, D. – National Center for Education Statistics, 2015
The School Composition and the Black-White Achievement Gap study was undertaken by the National Center for Education Statistics to present both descriptive and associative information on the relationships among the percentage of students in a school who were Black (referred to as "Black student density" or "density"), the…
Descriptors: School Demography, Racial Composition, Achievement Gap, African American Students
Hsieh, Chueh-an; Xu, Xueli; von Davier, Matthias – Educational Testing Service, 2010
This paper presents an application of a jackknifing approach to variance estimation of ability inferences for groups of students, using a multidimensional discrete model for item response data. The data utilized to demonstrate the approach come from the National Assessment of Educational Progress (NAEP). In contrast to the operational approach…
Descriptors: National Competency Tests, Reading Tests, Grade 4, Computation
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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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Oranje, Andreas; Li, Deping; Kandathil, Mathew – ETS Research Report Series, 2009
Several complex sample standard error estimators based on linearization and resampling for the latent regression model of the National Assessment of Educational Progress (NAEP) are studied with respect to design choices such as number of items, number of regressors, and the efficiency of the sample. This paper provides an evaluation of the extent…
Descriptors: Error of Measurement, Computation, Regression (Statistics), National Competency Tests
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Li, Deping; Oranje, Andreas; Jiang, Yanlin – Journal of Educational and Behavioral Statistics, 2009
To find population proficiency distributions, a two-level hierarchical linear model may be applied to large-scale survey assessments such as the National Assessment of Educational Progress (NAEP). The model and parameter estimation are developed and a simulation was carried out to evaluate parameter recovery. Subsequently, both a hierarchical and…
Descriptors: Computation, National Competency Tests, Measurement, Regression (Statistics)
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Xu, Xueli; von Davier, Matthias – ETS Research Report Series, 2008
The general diagnostic model (GDM) utilizes located latent classes for modeling a multidimensional proficiency variable. In this paper, the GDM is extended by employing a log-linear model for multiple populations that assumes constraints on parameters across multiple groups. This constrained model is compared to log-linear models that assume…
Descriptors: Comparative Analysis, Models, Computation, National Competency Tests
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Antal, Tamás – ETS Research Report Series, 2007
Full account of the latent regression model for the National Assessment of Educational Progress is given. The treatment includes derivation of the EM algorithm, Newton-Raphson method, and the asymptotic standard errors. The paper also features the use of the adaptive Gauss-Hermite numerical integration method as a basic tool to evaluate…
Descriptors: Regression (Statistics), Item Response Theory, National Competency Tests, Evaluation Methods
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Sinharay, Sandip; von Davier, Matthias – ETS Research Report Series, 2005
The reporting methods used in large scale assessments such as the National Assessment of Educational Progress (NAEP) rely on a "latent regression model." The first component of the model consists of a "p"-scale IRT measurement model that defines the response probabilities on a set of cognitive items in "p" scales…
Descriptors: National Competency Tests, Regression (Statistics), Predictor Variables, Student Characteristics