File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1007/s11336-015-9467-8
- Scopus: eid_2-s2.0-84928963861
- WOS: WOS:000377454400001
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: A General Method of Empirical Q-matrix Validation
Title | A General Method of Empirical Q-matrix Validation |
---|---|
Authors | |
Keywords | cognitive diagnosis |
Issue Date | 2016 |
Citation | Psychometrika, 2016, v. 81, n. 2, p. 253-273 How to Cite? |
Abstract | © 2015, The Psychometric Society.In contrast to unidimensional item response models that postulate a single underlying proficiency, cognitive diagnosis models (CDMs) posit multiple, discrete skills or attributes, thus allowing CDMs to provide a finer-grained assessment of examinees’ test performance. A common component of CDMs for specifying the attributes required for each item is the Q-matrix. Although construction of Q-matrix is typically performed by domain experts, it nonetheless, to a large extent, remains a subjective process, and misspecifications in the Q-matrix, if left unchecked, can have important practical implications. To address this concern, this paper proposes a discrimination index that can be used with a wide class of CDM subsumed by the generalized deterministic input, noisy “and” gate model to empirically validate the Q-matrix specifications by identifying and replacing misspecified entries in the Q-matrix. The rationale for using the index as the basis for a proposed validation method is provided in the form of mathematical proofs to several relevant lemmas and a theorem. The feasibility of the proposed method was examined using simulated data generated under various conditions. The proposed method is illustrated using fraction subtraction data. |
Persistent Identifier | http://hdl.handle.net/10722/228218 |
ISSN | 2023 Impact Factor: 2.9 2023 SCImago Journal Rankings: 2.376 |
ISI Accession Number ID |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | de la Torre, Jimmy | - |
dc.contributor.author | Chiu, Chia Yi | - |
dc.date.accessioned | 2016-08-01T06:45:29Z | - |
dc.date.available | 2016-08-01T06:45:29Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | Psychometrika, 2016, v. 81, n. 2, p. 253-273 | - |
dc.identifier.issn | 0033-3123 | - |
dc.identifier.uri | http://hdl.handle.net/10722/228218 | - |
dc.description.abstract | © 2015, The Psychometric Society.In contrast to unidimensional item response models that postulate a single underlying proficiency, cognitive diagnosis models (CDMs) posit multiple, discrete skills or attributes, thus allowing CDMs to provide a finer-grained assessment of examinees’ test performance. A common component of CDMs for specifying the attributes required for each item is the Q-matrix. Although construction of Q-matrix is typically performed by domain experts, it nonetheless, to a large extent, remains a subjective process, and misspecifications in the Q-matrix, if left unchecked, can have important practical implications. To address this concern, this paper proposes a discrimination index that can be used with a wide class of CDM subsumed by the generalized deterministic input, noisy “and” gate model to empirically validate the Q-matrix specifications by identifying and replacing misspecified entries in the Q-matrix. The rationale for using the index as the basis for a proposed validation method is provided in the form of mathematical proofs to several relevant lemmas and a theorem. The feasibility of the proposed method was examined using simulated data generated under various conditions. The proposed method is illustrated using fraction subtraction data. | - |
dc.language | eng | - |
dc.relation.ispartof | Psychometrika | - |
dc.subject | cognitive diagnosis | - |
dc.title | A General Method of Empirical Q-matrix Validation | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1007/s11336-015-9467-8 | - |
dc.identifier.scopus | eid_2-s2.0-84928963861 | - |
dc.identifier.volume | 81 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 253 | - |
dc.identifier.epage | 273 | - |
dc.identifier.isi | WOS:000377454400001 | - |
dc.identifier.issnl | 0033-3123 | - |