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Reardon, Sean F.; Ho, Andrew D.; Kalogrides, Demetra – Stanford Center for Education Policy Analysis, 2019
Linking score scales across different tests is considered speculative and fraught, even at the aggregate level (Feuer et al., 1999; Thissen, 2007). We introduce and illustrate validation methods for aggregate linkages, using the challenge of linking U.S. school district average test scores across states as a motivating example. We show that…
Descriptors: Test Validity, Evaluation Methods, School Districts, Scores
Stapleton, Laura M.; Kang, Yoonjeong – Sociological Methods & Research, 2018
This research empirically evaluates data sets from the National Center for Education Statistics (NCES) for design effects of ignoring the sampling design in weighted two-level analyses. Currently, researchers may ignore the sampling design beyond the levels that they model which might result in incorrect inferences regarding hypotheses due to…
Descriptors: Probability, Hierarchical Linear Modeling, Sampling, Inferences
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Pokropek, Artur – Sociological Methods & Research, 2015
This article combines statistical and applied research perspective showing problems that might arise when measurement error in multilevel compositional effects analysis is ignored. This article focuses on data where independent variables are constructed measures. Simulation studies are conducted evaluating methods that could overcome the…
Descriptors: Error of Measurement, Hierarchical Linear Modeling, Simulation, Evaluation Methods