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Mang, Julia; Küchenhoff, Helmut; Meinck, Sabine; Prenzel, Manfred – Large-scale Assessments in Education, 2021
Background: Standard methods for analysing data from large-scale assessments (LSA) cannot merely be adopted if hierarchical (or multilevel) regression modelling should be applied. Currently various approaches exist; they all follow generally a design-based model of estimation using the pseudo maximum likelihood method and adjusted weights for the…
Descriptors: Sampling, Hierarchical Linear Modeling, Simulation, Scaling
Papadimitropoulou, Katerina; Stijnen, Theo; Dekkers, Olaf M.; le Cessie, Saskia – Research Synthesis Methods, 2019
The vast majority of meta-analyses uses summary/aggregate data retrieved from published studies in contrast to meta-analysis of individual participant data (IPD). When the outcome is continuous and IPD are available, linear mixed modelling methods can be employed in a one-stage approach. This allows for flexible modelling of within-study…
Descriptors: Meta Analysis, Outcome Measures, Hierarchical Linear Modeling, Sample Size
Schoeneberger, Jason A. – Journal of Experimental Education, 2016
The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…
Descriptors: Sample Size, Models, Computation, Predictor Variables
Leckie, George; French, Robert; Charlton, Chris; Browne, William – Journal of Educational and Behavioral Statistics, 2014
Applications of multilevel models to continuous outcomes nearly always assume constant residual variance and constant random effects variances and covariances. However, modeling heterogeneity of variance can prove a useful indicator of model misspecification, and in some educational and behavioral studies, it may even be of direct substantive…
Descriptors: Hierarchical Linear Modeling, Statistical Analysis, Predictor Variables, Computer Software
Mayrose, James – American Journal of Engineering Education, 2012
Immersive Virtual Reality (VR) has seen explosive growth over the last decade. Immersive VR attempts to give users the sensation of being fully immersed in a synthetic environment by providing them with 3D hardware, and allowing them to interact with objects in virtual worlds. The technology is extremely effective for learning and exploration, and…
Descriptors: Active Learning, Educational Technology, Technology Uses in Education, Computer Simulation