Bias Corrections for Standardized Effect Size Estimates Used with Single-Subject Experimental Designs

Autor/inn/en	Ugille, Maaike; Moeyaert, Mariola; Beretvas, S. Natasha; Ferron, John M.; Van den Noortgate, Wim
Titel	Bias Corrections for Standardized Effect Size Estimates Used with Single-Subject Experimental Designs
Quelle	In: Journal of Experimental Education, 82 (2014) 3, S.358-374 (17 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	Weitere Informationen
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0022-0973
DOI	10.1080/00220973.2013.813366
Schlagwörter	Effect Size; Statistical Bias; Sample Size; Regression (Statistics); Statistical Inference; Sampling; Computation; Research Design; Meta Analysis; Simulation; Statistical Analysis; Intervention + Suchen Sie Ihr Suchwort? Regression; Regressionsanalyse; Inferential statistics; Schließende Statistik; Forschungsdesign; Meta-analysis; Metaanalyse; Simulation program; Simulationsprogramm; Statistische Analyse
Abstract	A multilevel meta-analysis can combine the results of several single-subject experimental design studies. However, the estimated effects are biased if the effect sizes are standardized and the number of measurement occasions is small. In this study, the authors investigated 4 approaches to correct for this bias. First, the standardized effect sizes are adjusted using Hedges' small sample bias correction. Next, the within-subject standard deviation is estimated by a 2-level model per study or by using a regression model with the subjects identified using dummy predictor variables. The effect sizes are corrected using an iterative raw data parametric bootstrap procedure. The results indicate that the first and last approach succeed in reducing the bias of the fixed effects estimates. Given the difference in complexity, we recommend the first approach. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10