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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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Ho, Andrew Dean – Journal of Educational and Behavioral Statistics, 2009
Problems of scale typically arise when comparing test score trends, gaps, and gap trends across different tests. To overcome some of these difficulties, test score distributions on the same score scale can be represented by nonparametric graphs or statistics that are invariant under monotone scale transformations. This article motivates and then…
Descriptors: Nonparametric Statistics, Comparative Analysis, Trend Analysis, Scores
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Xu, Xueli; von Davier, Matthias – ETS Research Report Series, 2008
Xu and von Davier (2006) demonstrated the feasibility of using the general diagnostic model (GDM) to analyze National Assessment of Educational Progress (NAEP) proficiency data. Their work showed that the GDM analysis not only led to conclusions for gender and race groups similar to those published in the NAEP Report Card, but also allowed…
Descriptors: National Competency Tests, Models, Data Analysis, Reading Tests
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Xu, Xueli; von Davier, Matthias – ETS Research Report Series, 2008
Three strategies for linking two consecutive assessments are investigated and compared by analyzing reading data for the National Assessment of Educational Progress (NAEP) using the general diagnostic model. These strategies are compared in terms of marginal and joint expectations of skills, joint probabilities of skill patterns, and item…
Descriptors: National Competency Tests, Probability, Reading Achievement, Test Items