{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/82007"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/82007","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"A Unifying Framework for the Analysis of Continuous and Discontinuous Change","abstract":"This thesis develops a new modeling framework, called generalized latent change modeling, as a unifying approach to investigate diverse patterns of change from a stage-sequential perspective. Whereas stage theories were originally proposed to describe discontinuous characteristics of human development, it is shown that stage-sequential change is not necessarily incompatible with continuous change. The family of generalized latent change models (GLCMs) integrates a number of well-known quantitative methods into a unified framework and offers a variety of new options. The new methodology accommodates both continuous and discontinuous change processes and can take into account a wide range of data types including continuous, binary, ordinal, categorical, frequency, ranking, and proportion data, as well as mixtures of response variables. As a result, this modeling approach offers a versatile and practical way of analyzing longitudinal data. Several empirical data analyses demonstrate that GLCMs yield easily interpretable results and provide important statistical tests for various hypotheses and competing theories about the behavioral change mechanism. The applications given include studies of attitude change toward substance use among adolescents and value change regarding the concept of a good citizen in the United States from the 1960s to the 1980s.","abstract_html":"This thesis develops a new modeling framework, called generalized latent change modeling, as a unifying approach to investigate diverse patterns of change from a stage-sequential perspective. Whereas stage theories were originally proposed to describe discontinuous characteristics of human development, it is shown that stage-sequential change is not necessarily incompatible with continuous change. The family of generalized latent change models (GLCMs) integrates a number of well-known quantitative methods into a unified framework and offers a variety of new options. The new methodology accommodates both continuous and discontinuous change processes and can take into account a wide range of data types including continuous, binary, ordinal, categorical, frequency, ranking, and proportion data, as well as mixtures of response variables. As a result, this modeling approach offers a versatile and practical way of analyzing longitudinal data. Several empirical data analyses demonstrate that GLCMs yield easily interpretable results and provide important statistical tests for various hypotheses and competing theories about the behavioral change mechanism. The applications given include studies of attitude change toward substance use among adolescents and value change regarding the concept of a good citizen in the United States from the 1960s to the 1980s.","abstract_has_math":false,"creators":["Kim, Jee-Seon"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Psychology","degree_department":null,"school":null,"contributors":["Bockenholt, Ulf","Hubert, Lawrence J."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-25T20:38:38Z","date_published":"2015-09-25T20:38:38Z","updated_at":"2026-07-22T22:26:17Z","subjects":["Biology, Biostatistics"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI3023092"],"render_values":[{"text":"(MiAaPQ)AAI3023092","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/82007","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Bockenholt, Ulf","Hubert, Lawrence J."]},{"key":"dc:creator","label":"Author","values":["Kim, Jee-Seon"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-25T20:38:38Z","10000-01-01","2001"]},{"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":["Biology, Biostatistics"]}]},{"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/2142/82007","(MiAaPQ)AAI3023092"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This thesis develops a new modeling framework, called generalized latent change modeling, as a unifying approach to investigate diverse patterns of change from a stage-sequential perspective. 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