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ERIC Number: EJ896948
Record Type: Journal
Publication Date: 2010-Oct
Pages: 16
Abstractor: As Provided
Reference Count: 31
ISSN: ISSN-0146-6216
An Extension of Least Squares Estimation of IRT Linking Coefficients for the Graded Response Model
Kim, Seonghoon
Applied Psychological Measurement, v34 n7 p505-520 Oct 2010
The three types (generalized, unweighted, and weighted) of least squares methods, proposed by Ogasawara, for estimating item response theory (IRT) linking coefficients under dichotomous models are extended to the graded response model. A simulation study was conducted to confirm the accuracy of the extended formulas, and a real data study was carried out to compare the performance of the least squares methods with that of moment and characteristic curve linking methods. As found in Ogasawara's study, the generalized least squares method had the smallest asymptotic standard errors but the largest biases of linking coefficient estimates, whereas the unweighted least squares method had the largest asymptotic standard errors but the smallest biases. The weighted least squares method was intermediate. The comparison study showed that with large samples, the weighted least squares method performed nearly as well as the characteristic curve methods in linking accuracy. (Contains 6 tables.)
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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