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Lee, HyeSun – Applied Measurement in Education, 2018
The current simulation study examined the effects of Item Parameter Drift (IPD) occurring in a short scale on parameter estimates in multilevel models where scores from a scale were employed as a time-varying predictor to account for outcome scores. Five factors, including three decisions about IPD, were considered for simulation conditions. It…
Descriptors: Test Items, Hierarchical Linear Modeling, Predictor Variables, 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
Jacob, Robin T.; Goddard, Roger D.; Kim, Eun Sook – Educational Evaluation and Policy Analysis, 2014
It is often difficult and costly to obtain individual-level student achievement data, yet, researchers are frequently reluctant to use school-level achievement data that are widely available from state websites. We argue that public-use aggregate school-level achievement data are, in fact, sufficient to address a wide range of evaluation questions…
Descriptors: Academic Achievement, Data, Information Utilization, Educational Assessment
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
Schweig, Jonathan – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2013
Measuring school and classroom environments has become central in a nation-wide effort to develop comprehensive programs that measure teacher quality and teacher effectiveness. Formulating successful programs necessitates accurate and reliable methods for measuring these environmental variables. This paper uses a generalizability theory framework…
Descriptors: Error of Measurement, Hierarchical Linear Modeling, Educational Environment, Classroom Environment