ERIC Number: EJ1028124
Record Type: Journal
Publication Date: 2014
Pages: 21
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0022-0973
EISSN: N/A
Three-Level Analysis of Single-Case Experimental Data: Empirical Validation
Moeyaert, Mariola; Ugille, Maaike; Ferron, John M.; Beretvas, S. Natasha; Van den Noortgate, Wim
Journal of Experimental Education, v82 n1 p1-21 2014
One approach for combining single-case data involves use of multilevel modeling. In this article, the authors use a Monte Carlo simulation study to inform applied researchers under which realistic conditions the three-level model is appropriate. The authors vary the value of the immediate treatment effect and the treatment's effect on the time trend, the number of studies, cases and measurements, and the between-case and between-study variance. The study shows that the three-level approach results in unbiased estimates of both kinds of treatment effects. To have reasonable power for testing the treatment effects, the authors recommend researchers to use a homogeneous set of studies and to involve a minimum of 30 studies. The number of measurements and cases is of less importance.
Descriptors: Hierarchical Linear Modeling, Monte Carlo Methods, Case Studies, Research Design, Statistical Bias, Computation, Error of Measurement, Statistical Analysis, Maximum Likelihood Statistics
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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
IES Funded: Yes
Grant or Contract Numbers: R305D110024