Power and Sample Size Calculations for Logistic Regression Tests for Differential Item Functioning

Autor/in	Li, Zhushan
Titel	Power and Sample Size Calculations for Logistic Regression Tests for Differential Item Functioning
Quelle	In: Journal of Educational Measurement, 51 (2014) 4, S.441-462 (22 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0022-0655
DOI	10.1111/jedm.12058
Schlagwörter	Test Bias; Sample Size; Statistical Analysis; Regression (Statistics); Simulation; Robustness (Statistics) + Suchen Sie Ihr Suchwort? Testkritik; Statistische Analyse; Regression; Regressionsanalyse; Simulation program; Simulationsprogramm; Widerstandsfähigkeit
Abstract	Logistic regression is a popular method for detecting uniform and nonuniform differential item functioning (DIF) effects. Theoretical formulas for the power and sample size calculations are derived for likelihood ratio tests and Wald tests based on the asymptotic distribution of the maximum likelihood estimators for the logistic regression model. The power is related to the item response function (IRF) for the studied item, the latent trait distributions, and the sample sizes for the reference and focal groups. Simulation studies show that the theoretical values calculated from the formulas derived in the article are close to what are observed in the simulated data when the assumptions are satisfied. The robustness of the power formulas are studied with simulations when the assumptions are violated. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10