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McNeish, Daniel M.; Stapleton, Laura M. – Educational Psychology Review, 2016
Multilevel models are an increasingly popular method to analyze data that originate from a clustered or hierarchical structure. To effectively utilize multilevel models, one must have an adequately large number of clusters; otherwise, some model parameters will be estimated with bias. The goals for this paper are to (1) raise awareness of the…
Descriptors: Hierarchical Linear Modeling, Statistical Analysis, Sample Size, Effect Size
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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