File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Evaluating the wald test for item-level comparison of saturated and reduced models in cognitive diagnosis

TitleEvaluating the wald test for item-level comparison of saturated and reduced models in cognitive diagnosis
Authors
Issue Date2013
Citation
Journal of Educational Measurement, 2013, v. 50, n. 4, p. 355-373 How to Cite?
AbstractThis article used the Wald test to evaluate the item-level fit of a saturated cognitive diagnosis model (CDM) relative to the fits of the reduced models it subsumes. A simulation study was carried out to examine the Type I error and power of the Wald test in the context of the G-DINA model. Results show that when the sample size is small and a larger number of attributes are required, the Type I error rate of the Wald test for the DINA and DINO models can be higher than the nominal significance levels, while the Type I error rate of the A-CDM is closer to the nominal significance levels. However, with larger sample sizes, the Type I error rates for the three models are closer to the nominal significance levels. In addition, the Wald test has excellent statistical power to detect when the true underlying model is none of the reduced models examined even for relatively small sample sizes. The performance of the Wald test was also examined with real data. With an increasing number of CDMs from which to choose, this article provides an important contribution toward advancing the use of CDMs in practical educational settings. © 2013 by the National Council on Measurement in Education.
Persistent Identifierhttp://hdl.handle.net/10722/228177
ISSN
2015 Impact Factor: 1.528
2015 SCImago Journal Rankings: 2.067

 

DC FieldValueLanguage
dc.contributor.authorDe la Torre, Jimmy-
dc.contributor.authorLee, Young Sun-
dc.date.accessioned2016-08-01T06:45:23Z-
dc.date.available2016-08-01T06:45:23Z-
dc.date.issued2013-
dc.identifier.citationJournal of Educational Measurement, 2013, v. 50, n. 4, p. 355-373-
dc.identifier.issn0022-0655-
dc.identifier.urihttp://hdl.handle.net/10722/228177-
dc.description.abstractThis article used the Wald test to evaluate the item-level fit of a saturated cognitive diagnosis model (CDM) relative to the fits of the reduced models it subsumes. A simulation study was carried out to examine the Type I error and power of the Wald test in the context of the G-DINA model. Results show that when the sample size is small and a larger number of attributes are required, the Type I error rate of the Wald test for the DINA and DINO models can be higher than the nominal significance levels, while the Type I error rate of the A-CDM is closer to the nominal significance levels. However, with larger sample sizes, the Type I error rates for the three models are closer to the nominal significance levels. In addition, the Wald test has excellent statistical power to detect when the true underlying model is none of the reduced models examined even for relatively small sample sizes. The performance of the Wald test was also examined with real data. With an increasing number of CDMs from which to choose, this article provides an important contribution toward advancing the use of CDMs in practical educational settings. © 2013 by the National Council on Measurement in Education.-
dc.languageeng-
dc.relation.ispartofJournal of Educational Measurement-
dc.titleEvaluating the wald test for item-level comparison of saturated and reduced models in cognitive diagnosis-
dc.typeArticle-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.1111/jedm.12022-
dc.identifier.scopuseid_2-s2.0-84892888153-
dc.identifier.volume50-
dc.identifier.issue4-
dc.identifier.spage355-
dc.identifier.epage373-
dc.identifier.eissn1745-3984-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats