Abstract
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.
Original language | English (US) |
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Pages (from-to) | 295-314 |
Number of pages | 20 |
Journal | Educational Psychology Review |
Volume | 28 |
Issue number | 2 |
DOIs | |
State | Published - Jun 1 2016 |
Externally published | Yes |
Keywords
- HLM
- Mixed model
- Multilevel model
- Small number of clusters
- Small sample
ASJC Scopus subject areas
- Developmental and Educational Psychology