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Article: A Residual-Based Approach to Validate Q-Matrix Specifications
Title | A Residual-Based Approach to Validate Q-Matrix Specifications |
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Authors | |
Keywords | validation residual based Q-matrix cognitive diagnosis model fit measure |
Issue Date | 2017 |
Citation | Applied Psychological Measurement, 2017, v. 41, n. 4, p. 277-293 How to Cite? |
Abstract | © 2017, © The Author(s) 2017. Q-matrix validation is of increasing concern due to the significance and subjective tendency of Q-matrix construction in the modeling process. This research proposes a residual-based approach to empirically validate Q-matrix specification based on a combination of fit measures. The approach separates Q-matrix validation into four logical steps, including the test-level evaluation, possible distinction between attribute-level and item-level misspecifications, identification of the hit item, and fit information to aid in item adjustment. Through simulation studies and real-life examples, it is shown that the misspecified items can be detected as the hit item and adjusted sequentially when the misspecification occurs at the item level or at random. Adjustment can be based on the maximum reduction of the test-level measures. When adjustment of individual items tends to be useless, attribute-level misspecification is of concern. The approach can accommodate a variety of cognitive diagnosis models (CDMs) and be extended to cover other response formats. |
Persistent Identifier | http://hdl.handle.net/10722/288851 |
ISSN | 2023 Impact Factor: 1.0 2023 SCImago Journal Rankings: 1.061 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Chen, Jinsong | - |
dc.date.accessioned | 2020-10-12T08:06:02Z | - |
dc.date.available | 2020-10-12T08:06:02Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Applied Psychological Measurement, 2017, v. 41, n. 4, p. 277-293 | - |
dc.identifier.issn | 0146-6216 | - |
dc.identifier.uri | http://hdl.handle.net/10722/288851 | - |
dc.description.abstract | © 2017, © The Author(s) 2017. Q-matrix validation is of increasing concern due to the significance and subjective tendency of Q-matrix construction in the modeling process. This research proposes a residual-based approach to empirically validate Q-matrix specification based on a combination of fit measures. The approach separates Q-matrix validation into four logical steps, including the test-level evaluation, possible distinction between attribute-level and item-level misspecifications, identification of the hit item, and fit information to aid in item adjustment. Through simulation studies and real-life examples, it is shown that the misspecified items can be detected as the hit item and adjusted sequentially when the misspecification occurs at the item level or at random. Adjustment can be based on the maximum reduction of the test-level measures. When adjustment of individual items tends to be useless, attribute-level misspecification is of concern. The approach can accommodate a variety of cognitive diagnosis models (CDMs) and be extended to cover other response formats. | - |
dc.language | eng | - |
dc.relation.ispartof | Applied Psychological Measurement | - |
dc.subject | validation | - |
dc.subject | residual based | - |
dc.subject | Q-matrix | - |
dc.subject | cognitive diagnosis model | - |
dc.subject | fit measure | - |
dc.title | A Residual-Based Approach to Validate Q-Matrix Specifications | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1177/0146621616686021 | - |
dc.identifier.scopus | eid_2-s2.0-85019030512 | - |
dc.identifier.volume | 41 | - |
dc.identifier.issue | 4 | - |
dc.identifier.spage | 277 | - |
dc.identifier.epage | 293 | - |
dc.identifier.eissn | 1552-3497 | - |
dc.identifier.isi | WOS:000406582500003 | - |
dc.identifier.issnl | 0146-6216 | - |