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Luo, Wen; Li, Haoran; Baek, Eunkyeng; Chen, Siqi; Lam, Kwok Hap; Semma, Brandie – Review of Educational Research, 2021
Multilevel modeling (MLM) is a statistical technique for analyzing clustered data. Despite its long history, the technique and accompanying computer programs are rapidly evolving. Given the complexity of multilevel models, it is crucial for researchers to provide complete and transparent descriptions of the data, statistical analyses, and results.…
Descriptors: Hierarchical Linear Modeling, Multivariate Analysis, Prediction, Research Problems
Van den Noortgate, Wim; Moeyaert, Mariola; Ugille, Maaike; Beretvas, Tasha; Ferron, John – Society for Research on Educational Effectiveness, 2014
Due to an increasing interest in the use of single-subject experimental designs (SSEDs), appropriate techniques are needed to analyze this type of data. The purpose of this paper proposal is to present four studies (Beretvas, Hembry, Van den Noortgate, & Ferron, 2013; Bunuan, Hembry & Beretvas, 2013; Moeyaert, Ugille, Ferron, Beretvas,…
Descriptors: Research Methodology, Simulation, Bias, Statistical Inference
Stapleton, Laura M.; McNeish, Daniel M.; Yang, Ji Seung – Educational Psychologist, 2016
Multilevel models are often used to evaluate hypotheses about relations among constructs when data are nested within clusters (Raudenbush & Bryk, 2002), although alternative approaches are available when analyzing nested data (Binder & Roberts, 2003; Sterba, 2009). The overarching goal of this article is to suggest when it is appropriate…
Descriptors: Hierarchical Linear Modeling, Data Analysis, Statistical Data, Multivariate Analysis