{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/82191"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/82191","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"An Item Response Unfolding Model for Graphic Rating Scales","abstract":"The graphic rating scale, a measurement tool used in many areas of psychology, usually takes a form of a fixed-length line segment, with both ends bounded and labeled as extreme responses. The raters mark somewhere on the line, and the length of the line segment from one endpoint to the mark is taken as the measure. An item response unfolding model is proposed to analyze the bounded continuous data collected with the graphic rating scale. The model has both location and dispersion parameters, and the item response function is developed based on the truncated normal density. The item parameters are estimated using maximum marginal likelihood estimation, and the standard errors of the estimates are computed from the observed information matrix. Simulation studies were conducted to investigate the behavior of the estimators in two simple versions of the model, one with only location parameters and the other with a common dispersion parameter. Survey data from the American National Election Study were used to demonstrate the application of the proposed model in studying people's opinions towards political figures or social groups in the 2008 presidential election.","abstract_html":"The graphic rating scale, a measurement tool used in many areas of psychology, usually takes a form of a fixed-length line segment, with both ends bounded and labeled as extreme responses. The raters mark somewhere on the line, and the length of the line segment from one endpoint to the mark is taken as the measure. An item response unfolding model is proposed to analyze the bounded continuous data collected with the graphic rating scale. The model has both location and dispersion parameters, and the item response function is developed based on the truncated normal density. The item parameters are estimated using maximum marginal likelihood estimation, and the standard errors of the estimates are computed from the observed information matrix. Simulation studies were conducted to investigate the behavior of the estimators in two simple versions of the model, one with only location parameters and the other with a common dispersion parameter. Survey data from the American National Election Study were used to demonstrate the application of the proposed model in studying people's opinions towards political figures or social groups in the 2008 presidential election.","abstract_has_math":false,"creators":["Liu, Ying"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Psychology","degree_department":null,"school":null,"contributors":["Chang, Hua-Hua"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-25T20:39:31Z","date_published":"2015-09-25T20:39:31Z","updated_at":"2026-07-22T22:26:17Z","subjects":["Psychology, Psychometrics"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI3392197"],"render_values":[{"text":"(MiAaPQ)AAI3392197","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/82191","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":["Liu, Ying"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-25T20:39:31Z","10000-01-01","2009"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Psychology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"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":["Psychology, Psychometrics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/82191","(MiAaPQ)AAI3392197"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The graphic rating scale, a measurement tool used in many areas of psychology, usually takes a form of a fixed-length line segment, with both ends bounded and labeled as extreme responses. 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The raters mark somewhere on the line, and the length of the line segment from one endpoint to the mark is taken as the measure. An item response unfolding model is proposed to analyze the bounded continuous data collected with the graphic rating scale. The model has both location and dispersion parameters, and the item response function is developed based on the truncated normal density. The item parameters are estimated using maximum marginal likelihood estimation, and the standard errors of the estimates are computed from the observed information matrix. Simulation studies were conducted to investigate the behavior of the estimators in two simple versions of the model, one with only location parameters and the other with a common dispersion parameter. 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