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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
Wang, Ze – Educational Psychology, 2015
Using data from the Trends in International Mathematics and Science Study (TIMSS) 2007, this study examined the big-fish-little-pond-effects (BFLPEs) in 49 countries. In this study, the effect of math ability on math self-concept was decomposed into a within- and a between-level components using implicit mean centring and the complex data…
Descriptors: Nonverbal Ability, Mathematics, Self Concept, Hierarchical Linear Modeling
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