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ERIC Number: EJ919604
Record Type: Journal
Publication Date: 2011
Pages: 20
Abstractor: As Provided
Reference Count: 11
ISSN: ISSN-0895-7347
Practical Application of a Synthetic Linking Function on Small-Sample Equating
Kim, Sooyeon; von Davier, Alina A.; Haberman, Shelby
Applied Measurement in Education, v24 n2 p95-114 2011
The synthetic function is a weighted average of the identity (the linking function for forms that are known to be completely parallel) and a traditional equating method. The purpose of the present study was to investigate the benefits of the synthetic function on small-sample equating using various real data sets gathered from different administrations of tests from a licensure testing program. We investigated the chained linear, Tucker, Levine, and mean equating methods, along with the identity and the synthetic functions with small samples (N = 19 to 70). The synthetic function did not perform as well as did other linear equating methods because test forms differed markedly in difficulty; thus, the use of the identity function produced substantial bias. The effectiveness of the synthetic function depended on the forms' similarity in difficulty. (Contains 6 tables, 4 footnotes and 2 figures.)
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Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A