{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/49806"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/49806","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"A stepwise test characteristic curve method to detect item parameter drift","abstract":"An important assumption of item response theory (IRT) based equating is that the item parameters should be invariant over different testing occasions. Sometimes, however, item parameters do not remain invariant due to factors other than sampling error, and this is termed item parameter drift (IPD). Several methods have been proposed to detect drifted items. However, most of the existing methods aim at detecting the drift in individual items, which may not be ideal when only the overall test characteristic curve (TCC) is of interest to the users. One such occasion in common practice is IRT-based true score equating, where the goal is to create a conversion table to make the two TCCs as close as possible. This paper introduces a stepwise test characteristic curve (Stepwise TCC) method to dynamically detect item parameter drift based on TCC without requirement to set any critical values. Comparisons were made between the new method and two commonly used existing methods under the three-parameter logistic model. Results show that the new method performed well in IPD detection.","abstract_html":"An important assumption of item response theory (IRT) based equating is that the item parameters should be invariant over different testing occasions. Sometimes, however, item parameters do not remain invariant due to factors other than sampling error, and this is termed item parameter drift (IPD). Several methods have been proposed to detect drifted items. However, most of the existing methods aim at detecting the drift in individual items, which may not be ideal when only the overall test characteristic curve (TCC) is of interest to the users. One such occasion in common practice is IRT-based true score equating, where the goal is to create a conversion table to make the two TCCs as close as possible. This paper introduces a stepwise test characteristic curve (Stepwise TCC) method to dynamically detect item parameter drift based on TCC without requirement to set any critical values. Comparisons were made between the new method and two commonly used existing methods under the three-parameter logistic model. Results show that the new method performed well in IPD detection.","abstract_has_math":false,"creators":["Guo, Rui"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.A.","degree_level":"Thesis","degree_discipline":"Psychology","degree_department":null,"school":null,"contributors":["Chang, Hua-Hua"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-05-30T17:18:39Z","date_published":"2014-05-30T17:18:39Z","updated_at":"2026-07-22T22:25:40Z","subjects":["item parameter drift","stepwise selection","test characteristic curve","item response theory","true score equating"],"languages":["en"],"rights":["Copyright 2014 Rui Guo"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/49806","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Chang, Hua-Hua"]},{"key":"dc:creator","label":"Author","values":["Guo, Rui"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2014-05-30T17:18:39Z","2016-09-22T20:59:03Z","2014-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Psychology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.A."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["item parameter drift","stepwise selection","test characteristic curve","item response theory","true score equating"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2014 Rui Guo"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/49806"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["An important assumption of item response theory (IRT) based equating is that the item parameters should be invariant over different testing occasions. Sometimes, however, item parameters do not remain invariant due to factors other than sampling error, and this is termed item parameter drift (IPD). Several methods have been proposed to detect drifted items. However, most of the existing methods aim at detecting the drift in individual items, which may not be ideal when only the overall test characteristic curve (TCC) is of interest to the users. One such occasion in common practice is IRT-based true score equating, where the goal is to create a conversion table to make the two TCCs as close as possible. This paper introduces a stepwise test characteristic curve (Stepwise TCC) method to dynamically detect item parameter drift based on TCC without requirement to set any critical values. Comparisons were made between the new method and two commonly used existing methods under the three-parameter logistic model. Results show that the new method performed well in IPD detection.","Item withdrawn by Laura Spradlin (lspradl2@illinois.edu) on 2014-02-20T19:57:14Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Rui_Guo.pdf: 430204 bytes, checksum: 9dd0477582bc3a08c06980d07816d817 (MD5)","Made available in DSpace on 2014-05-30T17:18:39Z (GMT). No. of bitstreams: 2 Rui_Guo.pdf: 430204 bytes, checksum: 9dd0477582bc3a08c06980d07816d817 (MD5) license.txt: 4056 bytes, checksum: fc49b1569abc9ffc6b611a0fa72a2214 (MD5)","Item marked as restricted to the 'Administrator' Group (id=1) by Seth Robbins (robbins.sd@gmail.com) on 2014-05-30T17:21:33Z Item is restricted until 2016-05-30T17:21:23Z","Restriction data tranferred 2014-07-01T11:39:42-05:00 Original Data Group with Access Administrator Release Date: 2016-05-30 12:21:23 UTC Reason: Author requested closed access (OA after 2yrs) in Vireo ETD system","Limited Restriction Lifted for Item 49857 on 2016-09-22T20:59:03Z."]},{"key":"dc:title","label":"Title","values":["A stepwise test characteristic curve method to detect item parameter drift"]}]}],"canonical_facts":{"dc:contributor":["Chang, Hua-Hua"],"dc:creator":["Guo, Rui"],"dc:date":["2014-05-30T17:18:39Z","2016-09-22T20:59:03Z","2014-05"],"dc:description":["An important assumption of item response theory (IRT) based equating is that the item parameters should be invariant over different testing occasions. Sometimes, however, item parameters do not remain invariant due to factors other than sampling error, and this is termed item parameter drift (IPD). Several methods have been proposed to detect drifted items. However, most of the existing methods aim at detecting the drift in individual items, which may not be ideal when only the overall test characteristic curve (TCC) is of interest to the users. One such occasion in common practice is IRT-based true score equating, where the goal is to create a conversion table to make the two TCCs as close as possible. This paper introduces a stepwise test characteristic curve (Stepwise TCC) method to dynamically detect item parameter drift based on TCC without requirement to set any critical values. Comparisons were made between the new method and two commonly used existing methods under the three-parameter logistic model. Results show that the new method performed well in IPD detection.","Item withdrawn by Laura Spradlin (lspradl2@illinois.edu) on 2014-02-20T19:57:14Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Rui_Guo.pdf: 430204 bytes, checksum: 9dd0477582bc3a08c06980d07816d817 (MD5)","Made available in DSpace on 2014-05-30T17:18:39Z (GMT). No. of bitstreams: 2 Rui_Guo.pdf: 430204 bytes, checksum: 9dd0477582bc3a08c06980d07816d817 (MD5) license.txt: 4056 bytes, checksum: fc49b1569abc9ffc6b611a0fa72a2214 (MD5)","Item marked as restricted to the 'Administrator' Group (id=1) by Seth Robbins (robbins.sd@gmail.com) on 2014-05-30T17:21:33Z Item is restricted until 2016-05-30T17:21:23Z","Restriction data tranferred 2014-07-01T11:39:42-05:00 Original Data Group with Access Administrator Release Date: 2016-05-30 12:21:23 UTC Reason: Author requested closed access (OA after 2yrs) in Vireo ETD system","Limited Restriction Lifted for Item 49857 on 2016-09-22T20:59:03Z."],"dc:identifier":["http://hdl.handle.net/2142/49806"],"dc:language":["en"],"dc:rights":["Copyright 2014 Rui Guo"],"dc:subject":["item parameter drift","stepwise selection","test characteristic curve","item response theory","true score equating"],"dc:title":["A stepwise test characteristic curve method to detect item parameter drift"],"dc:type":["text"],"thesis:degree_discipline":["Psychology"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.A."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:40Z"}