Item Purification Does Not Always Improve DIF Detection: A Counterexample with Angoff's Delta Plot
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| Title: | Item Purification Does Not Always Improve DIF Detection: A Counterexample with Angoff's Delta Plot |
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| Language: | English |
| Authors: | Magis, David, Facon, Bruno |
| Source: | Educational and Psychological Measurement. Apr 2013 73(2):293-311. |
| Availability: | SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: http://sagepub.com |
| Peer Reviewed: | Y |
| Page Count: | 19 |
| Publication Date: | 2013 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Early Childhood Education Preschool Education Kindergarten Primary Education |
| Descriptors: | Test Bias, Test Items, Statistical Analysis, Error of Measurement, Preschool Children, Kindergarten, Young Children, Down Syndrome, Mental Retardation, Tests |
| Assessment and Survey Identifiers: | Boehm Test of Basic Concepts |
| DOI: | 10.1177/0013164412451903 |
| ISSN: | 0013-1644 |
| Abstract: | Item purification is an iterative process that is often advocated as improving the identification of items affected by differential item functioning (DIF). With test-score-based DIF detection methods, item purification iteratively removes the items currently flagged as DIF from the test scores to get purified sets of items, unaffected by DIF. The purpose of this article is to highlight that item purification is not always useful and that a single run of the DIF method may return equally suitable results. Angoff's Delta plot is considered as a counterexample DIF method, with a recent improvement to the derivation of the classification threshold. Several possible item purification processes may be defined with this method, and all of them are compared through a simulation study and a real data set analysis. It appears that none of these purification processes clearly improves the Delta plot performance. A tentative explanation is drawn from the conceptual difference between the modified Delta plot and the other traditional DIF methods. (Contains 4 figures and 1 table.) |
| Abstractor: | As Provided |
| Number of References: | 36 |
| Entry Date: | 2014 |
| Accession Number: | EJ1010165 |
| Database: | ERIC |
| Abstract: | Item purification is an iterative process that is often advocated as improving the identification of items affected by differential item functioning (DIF). With test-score-based DIF detection methods, item purification iteratively removes the items currently flagged as DIF from the test scores to get purified sets of items, unaffected by DIF. The purpose of this article is to highlight that item purification is not always useful and that a single run of the DIF method may return equally suitable results. Angoff's Delta plot is considered as a counterexample DIF method, with a recent improvement to the derivation of the classification threshold. Several possible item purification processes may be defined with this method, and all of them are compared through a simulation study and a real data set analysis. It appears that none of these purification processes clearly improves the Delta plot performance. A tentative explanation is drawn from the conceptual difference between the modified Delta plot and the other traditional DIF methods. (Contains 4 figures and 1 table.) |
|---|---|
| ISSN: | 0013-1644 |
| DOI: | 10.1177/0013164412451903 |
