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Oranje, Andreas; Kolstad, Andrew – Journal of Educational and Behavioral Statistics, 2019
The design and psychometric methodology of the National Assessment of Educational Progress (NAEP) is constantly evolving to meet the changing interests and demands stemming from a rapidly shifting educational landscape. NAEP has been built on strong research foundations that include conducting extensive evaluations and comparisons before new…
Descriptors: National Competency Tests, Psychometrics, Statistical Analysis, Computation
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
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)
Antal, Tamás; Oranje, Andreas – ETS Research Report Series, 2007
Well-known numerical integration methods are applied to item response theory (IRT) with special emphasis on the estimation of the latent regression model of NAEP [National Assessment of Educational Progress]. An argument is made that the Gauss-Hermite rule enhanced with Cholesky decomposition and normal approximation of the response likelihood is…
Descriptors: Item Response Theory, Computation, Regression (Statistics), National Competency Tests
Bennett, Randy Elliot; Braswell, James; Oranje, Andreas; Sandene, Brent; Kaplan, Bruce; Yan, Fred – Journal of Technology, Learning, and Assessment, 2008
This article describes selected results from the Math Online (MOL) study, one of three field investigations sponsored by the National Center for Education Statistics (NCES) to explore the use of new technology in NAEP. Of particular interest in the MOL study was the comparability of scores from paper- and computer-based tests. A nationally…
Descriptors: National Competency Tests, Familiarity, Computer Assisted Testing, Mathematics Tests
Oranje, Andreas – ETS Research Report Series, 2006
Confidence intervals are an important tool to indicate uncertainty of estimates and to give an idea of probable values of an estimate if a different sample from the population was drawn or a different sample of measures was used. Standard symmetric confidence intervals for proportion estimates based on a normal approximation can yield bounds…
Descriptors: Computation, Statistical Analysis, National Competency Tests, Comparative Analysis
Li, Deping; Oranje, Andreas – ETS Research Report Series, 2007
Two versions of a general method for approximating standard error of regression effect estimates within an IRT-based latent regression model are compared. The general method is based on Binder's (1983) approach, accounting for complex samples and finite populations by Taylor series linearization. In contrast, the current National Assessment of…
Descriptors: Error of Measurement, Regression (Statistics), Trend Analysis, National Competency Tests
Oranje, Andreas – ETS Research Report Series, 2006
A multitude of methods has been proposed to estimate the sampling variance of ratio estimates in complex samples (Wolter, 1985). Hansen and Tepping (1985) studied some of those variance estimators and found that a high coefficient of variation (CV) of the denominator of a ratio estimate is indicative of a biased estimate of the standard error of a…
Descriptors: Statistical Analysis, Computation, Sampling, Statistical Bias
Oranje, Andreas; Freund, David; Lin, Mei-jang; Tang, Yuxin – ETS Research Report Series, 2007
In this paper, a data perturbation method for minimizing the possibility of disclosure of participants' identities on a survey is described in the context of the National Assessment of Educational Progress (NAEP). The method distinguishes itself from most approaches because of the presence of cognitive tasks. Hence, a data edit should have minimal…
Descriptors: Student Surveys, Risk, National Competency Tests, Data Analysis
Deping, Li; Oranje, Andreas – ETS Research Report Series, 2006
A hierarchical latent regression model is suggested to estimate nested and nonnested relationships in complex samples such as found in the National Assessment of Educational Progress (NAEP). The proposed model aims at improving both parameters and variance estimates via a two-level hierarchical linear model. This model falls naturally within the…
Descriptors: Hierarchical Linear Modeling, Computation, Measurement, Regression (Statistics)
Sandene, Brent; Horkay, Nancy; Bennett, Randy Elliot; Allen, Nancy; Braswell, James; Kaplan, Bruce; Oranje, Andreas – National Center for Education Statistics, 2005
This publication presents the reports from two studies, Math Online (MOL) and Writing Online (WOL), part of the National Assessment of Educational Progress (NAEP) Technology-Based Assessment (TBA) project. Funded by the National Center for Education Statistics (NCES), the Technology-Based Assessment project is intended to explore the use of new…
Descriptors: Grade 8, Statistical Analysis, Scoring, Familiarity