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ERIC Number: EJ1047486
Record Type: Journal
Publication Date: 2014
Pages: 22
Abstractor: As Provided
ISSN: ISSN-0022-0655
Power and Sample Size Calculations for Logistic Regression Tests for Differential Item Functioning
Li, Zhushan
Journal of Educational Measurement, v51 n4 p441-462 Win 2014
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.
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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
Grant or Contract Numbers: N/A