Estimating Partial Standardized Mean Differences from Regression Models

Autor/inn/en	Aloe, Ariel M.; Thompson, Christopher G.; Liu, Zhijiang; Lin, Lifeng
Titel	Estimating Partial Standardized Mean Differences from Regression Models
Quelle	In: Journal of Experimental Education, 90 (2022) 4, S.898-915 (18 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0022-0973
DOI	10.1080/00220973.2021.1966605
Schlagwörter	Effect Size; Meta Analysis; Quasiexperimental Design; Regression (Statistics); Models + Suchen Sie Ihr Suchwort? Meta-analysis; Metaanalyse; Regression; Regressionsanalyse; Analogiemodell
Abstract	The distribution of the standardized mean difference is well understood. However, in many situations, researchers need to estimate an effect size to represent the relationship between a continuous outcome and a dichotomous grouping variable, adjusting for the effect of a covariate (or a set of covariates). Typically, this adjustment takes place via regression models. In this article, we consider five different estimators of standardized mean differences that could arise from regression models with one or more covariates. We demonstrate that an existing correction, believed to recover the pooled standard deviation, is in fact an approximation. In addition, we compared the performance of each standardized mean difference index. The function used to generate the data for the simulation is available in the Supplemental Material. Implications for comparing results from primary studies, as well as for meta-analysis, are also considered. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01