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The Effect of Small Sample Size on Two-Level Model Estimates: A Review and Illustration
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...
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| Published in: | Educational psychology review 2016-06, Vol.28 (2), p.295-314 |
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| Language: | English |
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| container_end_page | 314 |
| container_issue | 2 |
| container_start_page | 295 |
| container_title | Educational psychology review |
| container_volume | 28 |
| creator | McNeish, Daniel M. Stapleton, Laura M. |
| description | 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. |
| doi_str_mv | 10.1007/s10648-014-9287-x |
| format | article |
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| source | JSTOR Archival Journals and Primary Sources Collection【Remote access available】; Social Science Premium Collection; Springer Nature; ERIC; Education Collection |
| subjects | Child and School Psychology Cluster Grouping Data analysis Education Educational aspects Educational Psychology Effect Size Estimation bias Estimation methods Hierarchical Linear Modeling Learning and Instruction Least Squares Statistics Literature Reviews Maximum likelihood estimation Maximum Likelihood Statistics Multilevel models Multivariate Analysis Population estimates Research methods Research Problems Review Article REVIEW ARTICLES Sample Size Sampling distributions Simulation Simulations Standard error Statistical Analysis Statistical variance Studies |
| title | The Effect of Small Sample Size on Two-Level Model Estimates: A Review and Illustration |
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