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Julian F. Lohmann; Steffen Zitzmann; Martin Hecht – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The recently proposed "continuous-time latent curve model with structured residuals" (CT-LCM-SR) addresses several challenges associated with longitudinal data analysis in the behavioral sciences. First, it provides information about process trends and dynamics. Second, using the continuous-time framework, the CT-LCM-SR can handle…
Descriptors: Time Management, Behavioral Science Research, Predictive Validity, Predictor Variables
McNeish, Daniel; Bauer, Daniel J. – Grantee Submission, 2020
Deciding which random effects to retain is a central decision in mixed effect models. Recent recommendations advise a maximal structure whereby all theoretically relevant random effects are retained. Nonetheless, including many random effects often leads to nonpositive definiteness. A typical remedy is to simplify the random effect structure by…
Descriptors: Multivariate Analysis, Hierarchical Linear Modeling, Factor Analysis, Matrices
Enders, Craig K.; Keller, Brian T.; Levy, Roy – Grantee Submission, 2018
Specialized imputation routines for multilevel data are widely available in software packages, but these methods are generally not equipped to handle a wide range of complexities that are typical of behavioral science data. In particular, existing imputation schemes differ in their ability to handle random slopes, categorical variables,…
Descriptors: Hierarchical Linear Modeling, Behavioral Science Research, Computer Software, Bayesian Statistics
Lai, Mark H. C.; Kwok, Oi-Man – Journal of Educational and Behavioral Statistics, 2014
Multilevel modeling techniques are becoming more popular in handling data with multilevel structure in educational and behavioral research. Recently, researchers have paid more attention to cross-classified data structure that naturally arises in educational settings. However, unlike traditional single-level research, methodological studies about…
Descriptors: Hierarchical Linear Modeling, Differences, Effect Size, Computation
Tipton, Elizabeth; Yeager, David; Iachan, Ronaldo – Society for Research on Educational Effectiveness, 2016
Questions regarding the generalizability of results from educational experiments have been at the forefront of methods development over the past five years. This work has focused on methods for estimating the effect of an intervention in a well-defined inference population (e.g., Tipton, 2013; O'Muircheartaigh and Hedges, 2014); methods for…
Descriptors: Behavioral Sciences, Behavioral Science Research, Intervention, Educational Experiments
Roman, Caterina G.; Taylor, Caitlin J. – Journal of School Health, 2013
Background: This study integrated criminological and public health perspectives to examine the influence of bullying victimization and the school environment on physical activity (PA). Methods: We used a weighted sample of 7786 US middle school students surveyed as part of the Health Behavior in School-Aged Children study to conduct a multilevel…
Descriptors: Physical Activities, Educational Environment, Bullying, Criminology