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Grund, Simon; Lüdtke, Oliver; Robitzsch, Alexander – Journal of Educational and Behavioral Statistics, 2021
Large-scale assessments (LSAs) use Mislevy's "plausible value" (PV) approach to relate student proficiency to noncognitive variables administered in a background questionnaire. This method requires background variables to be completely observed, a requirement that is seldom fulfilled. In this article, we evaluate and compare the…
Descriptors: Data Analysis, Error of Measurement, Research Problems, Statistical Inference
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Longford, Nicholas T. – Journal of Educational and Behavioral Statistics, 2012
Statistical modeling of school effectiveness data was originally motivated by the dissatisfaction with the analysis of (school-leaving) examination results that took no account of the background of the students or regarded each school as an isolated unit of analysis. The application of multilevel analysis was generally regarded as a breakthrough,…
Descriptors: School Effectiveness, Data Analysis, Statistical Analysis, Statistical Studies
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Moses, Tim – Journal of Educational and Behavioral Statistics, 2008
Equating functions are supposed to be population invariant, meaning that the choice of subpopulation used to compute the equating function should not matter. The extent to which equating functions are population invariant is typically assessed in terms of practical difference criteria that do not account for equating functions' sampling…
Descriptors: Equated Scores, Error of Measurement, Sampling, Evaluation Methods
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Camilli, Gregory – Journal of Educational and Behavioral Statistics, 2006
A simple errors-in-variables regression model is given in this article for illustrating the method of marginal maximum likelihood (MML). Given suitable estimates of reliability, error variables, as nuisance variables, can be integrated out of likelihood equations. Given the closed form expression of the resulting marginal likelihood, the effects…
Descriptors: Maximum Likelihood Statistics, Regression (Statistics), Reliability, Error of Measurement
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Zwick, Rebecca; Thayer, Dorothy T. – Journal of Educational and Behavioral Statistics, 1996
Two possible standard error formulas for the polytomous differential item functioning index proposed by N. J. Dorans and A. P. Schmitt (1991) were derived. These standard errors, and associated hypothesis-testing procedures, were evaluated through simulated data. The standard error that performed better is based on N. Mantel's (1963)…
Descriptors: Error of Measurement, Evaluation Methods, Hypothesis Testing, Item Bias