ERIC Number: EJ1100669
Record Type: Journal
Publication Date: 2016-Jun
Abstractor: As Provided
Reference Count: 51
The Effect of Small Sample Size on Two-Level Model Estimates: A Review and Illustration
McNeish, Daniel M.; Stapleton, Laura M.
Educational Psychology Review, v28 n2 p295-314 Jun 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 problems associated with a small number of clusters, (2) review previous studies on multilevel models with a small number of clusters, (3) to provide an illustrative simulation to demonstrate how a simple model becomes adversely affected by small numbers of clusters, (4) to provide researchers with remedies if they encounter clustered data with a small number of clusters, and (5) to outline methodological topics that have yet to be addressed in the literature.
Descriptors: Hierarchical Linear Modeling, Statistical Analysis, Sample Size, Effect Size, Multivariate Analysis, Cluster Grouping, Literature Reviews, Simulation, Research Problems
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Publication Type: Journal Articles; Information Analyses; Reports - Evaluative
Education Level: N/A
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