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ERIC Number: EJ1086432
Record Type: Journal
Publication Date: 2016
Pages: 25
Abstractor: As Provided
ISSN: ISSN-0022-0973
The Impact of Sample Size and Other Factors When Estimating Multilevel Logistic Models
Schoeneberger, Jason A.
Journal of Experimental Education, v84 n2 p373-397 2016
The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying methods of estimation, level-1 and level-2 sample size, outcome prevalence, variance component sizes, and number of predictors using SAS software. Mean estimates of statistical power were influenced primarily by sample sizes at both levels. In addition, confidence interval coverage and width and the likelihood of nonpositive definite random effect covariance matrices were impacted by variance component size and estimation method. The interactions of these and other factors with various model performance outcomes are explored.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A