{"id":{"repo_id":"york","oai_identifier":"oai:yorkspace.library.yorku.ca:10315/38748"},"canonical_url":"https://search.dev.ndltd.org/etd/york/oai:yorkspace.library.yorku.ca:10315/38748","repository":{"repo_id":"york","name":"York University","base_url":"https://yorkspace.library.yorku.ca/oai/request"},"display":{"title":"When what is wrong seems right: A Monte Carlo simulation investigating the robustness of coefficient omega to model misspecification","abstract":"Coefficient omega is a model-based reliability estimate that is unrestricted by assumptions of a unidimensional essentially tau equivalent model. Rather, omega can be adapted to suit the underlying factor structure of a given population. A Monte Carlo simulation was used to investigate the performance of unidimensional omega and omega-hierarchical under circumstances of model misspecification for high and low reliability measures and different scale lengths. In general, bias increased with the amount of unmodeled complexity (i.e. unspecified multidimensionality or error correlations). When models were misspecified, observed bias was higher when true population reliability was lower, and increased with scale length. Less variable estimates were observed when true reliability and sample size were higher.","abstract_html":"Coefficient omega is a model-based reliability estimate that is unrestricted by assumptions of a unidimensional essentially tau equivalent model. Rather, omega can be adapted to suit the underlying factor structure of a given population. A Monte Carlo simulation was used to investigate the performance of unidimensional omega and omega-hierarchical under circumstances of model misspecification for high and low reliability measures and different scale lengths. In general, bias increased with the amount of unmodeled complexity (i.e. unspecified multidimensionality or error correlations). When models were misspecified, observed bias was higher when true population reliability was lower, and increased with scale length. Less variable estimates were observed when true reliability and sample size were higher.","abstract_has_math":false,"creators":["Bell, Stephanie Marie"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Flora, David B."],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-11-15","date_published":"2021-11-15","updated_at":"2026-07-24T06:33:43Z","subjects":["psychometrics"],"languages":["en"],"rights":["Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10315/38748","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Flora, David B."]},{"key":"dc:creator","label":"Author","values":["Bell, Stephanie Marie"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2021-11-15T15:35:42Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2021-11-15T15:35:42Z"]},{"key":"dc:date.issued","label":"Date","values":["2021-11-15"]},{"key":"dc:type","label":"Dc Type","values":["Electronic Thesis or Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["psychometrics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10315/38748"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Coefficient omega is a model-based reliability estimate that is unrestricted by assumptions of a unidimensional essentially tau equivalent model. Rather, omega can be adapted to suit the underlying factor structure of a given population. A Monte Carlo simulation was used to investigate the performance of unidimensional omega and omega-hierarchical under circumstances of model misspecification for high and low reliability measures and different scale lengths. In general, bias increased with the amount of unmodeled complexity (i.e. unspecified multidimensionality or error correlations). When models were misspecified, observed bias was higher when true population reliability was lower, and increased with scale length. Less variable estimates were observed when true reliability and sample size were higher."]},{"key":"dc:title","label":"Title","values":["When what is wrong seems right: A Monte Carlo simulation investigating the robustness of coefficient omega to model misspecification"]}]}],"canonical_facts":{"dc:contributor.advisor":["Flora, David B."],"dc:creator":["Bell, Stephanie Marie"],"dc:date.accessioned":["2021-11-15T15:35:42Z"],"dc:date.available":["2021-11-15T15:35:42Z"],"dc:date.issued":["2021-11-15"],"dc:description.abstract":["Coefficient omega is a model-based reliability estimate that is unrestricted by assumptions of a unidimensional essentially tau equivalent model. Rather, omega can be adapted to suit the underlying factor structure of a given population. A Monte Carlo simulation was used to investigate the performance of unidimensional omega and omega-hierarchical under circumstances of model misspecification for high and low reliability measures and different scale lengths. In general, bias increased with the amount of unmodeled complexity (i.e. unspecified multidimensionality or error correlations). When models were misspecified, observed bias was higher when true population reliability was lower, and increased with scale length. Less variable estimates were observed when true reliability and sample size were higher."],"dc:identifier.uri":["http://hdl.handle.net/10315/38748"],"dc:language":["en"],"dc:rights":["Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests."],"dc:subject":["psychometrics"],"dc:title":["When what is wrong seems right: A Monte Carlo simulation investigating the robustness of coefficient omega to model misspecification"],"dc:type":["Electronic Thesis or Dissertation"]},"updated_at":"2026-07-24T06:33:43Z"}