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Oliver Lüdtke; Alexander Robitzsch – Journal of Experimental Education, 2025
There is a longstanding debate on whether the analysis of covariance (ANCOVA) or the change score approach is more appropriate when analyzing non-experimental longitudinal data. In this article, we use a structural modeling perspective to clarify that the ANCOVA approach is based on the assumption that all relevant covariates are measured (i.e.,…
Descriptors: Statistical Analysis, Longitudinal Studies, Error of Measurement, Hierarchical Linear Modeling
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Sales, Adam; Prihar, Ethan; Heffernan, Neil; Pane, John F. – International Educational Data Mining Society, 2021
This paper drills deeper into the documented effects of the Cognitive Tutor Algebra I and ASSISTments intelligent tutoring systems by estimating their effects on specific problems. We start by describing a multilevel Rasch-type model that facilitates testing for differences in the effects between problems and precise problem-specific effect…
Descriptors: Intelligent Tutoring Systems, Academic Achievement, Educational Technology, Algebra
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Stallasch, Sophie E.; Lüdtke, Oliver; Artelt, Cordula; Brunner, Martin – Journal of Research on Educational Effectiveness, 2021
To plan cluster-randomized trials with sufficient statistical power to detect intervention effects on student achievement, researchers need multilevel design parameters, including measures of between-classroom and between-school differences and the amounts of variance explained by covariates at the student, classroom, and school level. Previous…
Descriptors: Foreign Countries, Randomized Controlled Trials, Intervention, Educational Research