Three-Level Analysis of Single-Case Experimental Data: Empirical Validation

Autor/inn/en	Moeyaert, Mariola; Ugille, Maaike; Ferron, John M.; Beretvas, S. Natasha; Van den Noortgate, Wim
Titel	Three-Level Analysis of Single-Case Experimental Data: Empirical Validation
Quelle	In: Journal of Experimental Education, 82 (2014) 1, S.1-21 (21 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	Weitere Informationen
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0022-0973
DOI	10.1080/00220973.2012.745470
Schlagwörter	Hierarchical Linear Modeling; Monte Carlo Methods; Case Studies; Research Design; Statistical Bias; Computation; Error of Measurement; Statistical Analysis; Maximum Likelihood Statistics + Suchen Sie Ihr Suchwort? Monte-Carlo-Methode; Case study; Fallstudie; Case Study; Forschungsdesign; Messfehler; Statistische Analyse
Abstract	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. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10