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ERIC Number: EJ1018963
Record Type: Journal
Publication Date: 2013-Oct
Pages: 19
Abstractor: As Provided
ISSN: ISSN-0146-6216
Using a Linear Regression Method to Detect Outliers in IRT Common Item Equating
He, Yong; Cui, Zhongmin; Fang, Yu; Chen, Hanwei
Applied Psychological Measurement, v37 n7 p522-540 Oct 2013
Common test items play an important role in equating alternate test forms under the common item nonequivalent groups design. When the item response theory (IRT) method is applied in equating, inconsistent item parameter estimates among common items can lead to large bias in equated scores. It is prudent to evaluate inconsistency in parameter estimates of common items before conducting IRT equating. The evaluation of inconsistency in parameter estimates is typically achieved through detecting outliers in the common item set. In this study, a linear regression method is proposed as a detection method. The newly proposed method was compared with a traditional method in various conditions. The results of this study confirmed the necessity of detecting and removing outlying common items. The results also show that the newly proposed method performed better than did the traditional method in most conditions.
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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