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Stapleton, Laura M.; Yang, Ji Seung; Hancock, Gregory R. – Journal of Educational and Behavioral Statistics, 2016
We present types of constructs, individual- and cluster-level, and their confirmatory factor analytic validation models when data are from individuals nested within clusters. When a construct is theoretically individual level, spurious construct-irrelevant dependency in the data may appear to signal cluster-level dependency; in such cases,…
Descriptors: Multivariate Analysis, Factor Analysis, Validity, Models
Kelcey, Benjamin; Dong, Nianbo; Spybrook, Jessaca; Cox, Kyle – Journal of Educational and Behavioral Statistics, 2017
Designs that facilitate inferences concerning both the total and indirect effects of a treatment potentially offer a more holistic description of interventions because they can complement "what works" questions with the comprehensive study of the causal connections implied by substantive theories. Mapping the sensitivity of designs to…
Descriptors: Statistical Analysis, Randomized Controlled Trials, Mediation Theory, Models
Drechsler, Jörg – Journal of Educational and Behavioral Statistics, 2015
Multiple imputation is widely accepted as the method of choice to address item-nonresponse in surveys. However, research on imputation strategies for the hierarchical structures that are typically found in the data in educational contexts is still limited. While a multilevel imputation model should be preferred from a theoretical point of view if…
Descriptors: Hierarchical Linear Modeling, Statistical Analysis, Educational Research, Statistical Bias
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
Sweet, Tracy M.; Thomas, Andrew C.; Junker, Brian W. – Journal of Educational and Behavioral Statistics, 2013
Intervention studies in school systems are sometimes aimed not at changing curriculum or classroom technique, but rather at changing the way that teachers, teaching coaches, and administrators in schools work with one another--in short, changing the professional social networks of educators. Current methods of social network analysis are…
Descriptors: Educational Research, Models, Social Networks, Network Analysis
Karl, Andrew T.; Yang, Yan; Lohr, Sharon L. – Journal of Educational and Behavioral Statistics, 2013
Value-added models have been widely used to assess the contributions of individual teachers and schools to students' academic growth based on longitudinal student achievement outcomes. There is concern, however, that ignoring the presence of missing values, which are common in longitudinal studies, can bias teachers' value-added scores.…
Descriptors: Evaluation Methods, Teacher Effectiveness, Academic Achievement, Achievement Gains