File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: Adopting the Multi-process Approach to Detect Differential Item Functioning in Likert Scales

TitleAdopting the Multi-process Approach to Detect Differential Item Functioning in Likert Scales
Authors
KeywordsIRTree
Differential item functioning
Logistic regression
Odds ratio
Purification
Issue Date2019
PublisherSpringer.
Citation
Quantitative Psychology: 83rd Annual Meeting of the Psychometric Society, New York, 9-13 July 2018. In Quantitative Psychology: 83rd Annual Meeting of the Psychometric Society, New York, NY 2018, p. 307-317 How to Cite?
AbstractThe current study compared the performance of the logistic regression (LR) and the odds ratio (OR) approaches in differential item functioning (DIF) detection in which the three processes of an IRTree model were considered in a five-point response scale. Three sets of binary pseudo items (BPI) were generated to indicate an intention of endorsing the midpoint response, a positive/negative attitude toward an item, and a tendency of using extreme category, respectively. Missing values inevitably appeared in the last two sets of BPI. We manipulated the DIF patterns, the percentages of DIF items, and the purification procedure (with/without). The results suggested that (1) both the LR and OR performed well in detecting DIF when BPI did not include missing values; (2) the OR method generally outperformed the LR method when BPI included missing values; (3) the OR method performed fairly well without a purification procedure, but the purification procedure improved the performance of the LR approach, especially when the number of DIF was large.
Persistent Identifierhttp://hdl.handle.net/10722/273482
ISBN
ISSN
Series/Report no.Springer Proceedings in Mathematics & Statistics

 

DC FieldValueLanguage
dc.contributor.authorJin, KY-
dc.contributor.authorWu, YJ-
dc.contributor.authorChen, HF-
dc.date.accessioned2019-08-06T09:29:48Z-
dc.date.available2019-08-06T09:29:48Z-
dc.date.issued2019-
dc.identifier.citationQuantitative Psychology: 83rd Annual Meeting of the Psychometric Society, New York, 9-13 July 2018. In Quantitative Psychology: 83rd Annual Meeting of the Psychometric Society, New York, NY 2018, p. 307-317-
dc.identifier.isbn9783030013097-
dc.identifier.issn2194-1009-
dc.identifier.urihttp://hdl.handle.net/10722/273482-
dc.description.abstractThe current study compared the performance of the logistic regression (LR) and the odds ratio (OR) approaches in differential item functioning (DIF) detection in which the three processes of an IRTree model were considered in a five-point response scale. Three sets of binary pseudo items (BPI) were generated to indicate an intention of endorsing the midpoint response, a positive/negative attitude toward an item, and a tendency of using extreme category, respectively. Missing values inevitably appeared in the last two sets of BPI. We manipulated the DIF patterns, the percentages of DIF items, and the purification procedure (with/without). The results suggested that (1) both the LR and OR performed well in detecting DIF when BPI did not include missing values; (2) the OR method generally outperformed the LR method when BPI included missing values; (3) the OR method performed fairly well without a purification procedure, but the purification procedure improved the performance of the LR approach, especially when the number of DIF was large.-
dc.languageeng-
dc.publisherSpringer.-
dc.relation.ispartofQuantitative Psychology: 83rd Annual Meeting of the Psychometric Society, New York, NY 2018-
dc.relation.ispartofseriesSpringer Proceedings in Mathematics & Statistics-
dc.rightsThis is a post-peer-review, pre-copyedit version of an article published in [insert journal title]. The final authenticated version is available online at: http://dx.doi.org/[insert DOI]-
dc.subjectIRTree-
dc.subjectDifferential item functioning-
dc.subjectLogistic regression-
dc.subjectOdds ratio-
dc.subjectPurification-
dc.titleAdopting the Multi-process Approach to Detect Differential Item Functioning in Likert Scales-
dc.typeConference_Paper-
dc.identifier.emailJin, KY: kyjin@hku.hk-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/978-3-030-01310-3_27-
dc.identifier.scopuseid_2-s2.0-85066085015-
dc.identifier.hkuros300789-
dc.identifier.spage307-
dc.identifier.epage317-
dc.identifier.eissn2194-1017-
dc.publisher.placeCham, Switzerland-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats