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Bolin, Jocelyn H.; Finch, W. Holmes; Stenger, Rachel – Educational and Psychological Measurement, 2019
Multilevel data are a reality for many disciplines. Currently, although multiple options exist for the treatment of multilevel data, most disciplines strictly adhere to one method for multilevel data regardless of the specific research design circumstances. The purpose of this Monte Carlo simulation study is to compare several methods for the…
Descriptors: Hierarchical Linear Modeling, Computation, Statistical Analysis, Maximum Likelihood Statistics
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Hembry, Ian; Bunuan, Rommel; Beretvas, S. Natasha; Ferron, John M.; Van den Noortgate, Wim – Journal of Experimental Education, 2015
A multilevel logistic model for estimating a nonlinear trajectory in a multiple-baseline design is introduced. The model is applied to data from a real multiple-baseline design study to demonstrate interpretation of relevant parameters. A simple change-in-levels (?"Levels") model and a model involving a quadratic function…
Descriptors: Computation, Research Design, Data, Intervention
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McNeish, Daniel M. – Journal of Educational and Behavioral Statistics, 2016
Mixed-effects models (MEMs) and latent growth models (LGMs) are often considered interchangeable save the discipline-specific nomenclature. Software implementations of these models, however, are not interchangeable, particularly with small sample sizes. Restricted maximum likelihood estimation that mitigates small sample bias in MEMs has not been…
Descriptors: Models, Statistical Analysis, Hierarchical Linear Modeling, Sample Size
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Espelage, Dorothy L.; Rose, Chad A.; Polanin, Joshua R. – Remedial and Special Education, 2015
Results of a 3-year randomized clinical trial of Second Step: Student Success Through Prevention (SS-SSTP) Middle School Program on reducing bullying, physical aggression, and peer victimization among students with disabilities are presented. Teachers implemented 41 lessons of a sixth- to eighth-grade curriculum that focused on social-emotional…
Descriptors: Bullying, Middle School Students, Disabilities, Victims
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Huang, Hung-Yu; Wang, Wen-Chung – Educational and Psychological Measurement, 2014
In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…
Descriptors: Item Response Theory, Hierarchical Linear Modeling, Computation, Test Reliability