{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/69904"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/69904","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Variations in Journey-to-Work Time, Distance and Speed Across Metropolitan Areas","abstract":"Variations in travel time, distance, and speed are identified for four Standard Metropolitan Statistical Areas. The unit of analysis consists of the journey-to-work for household heads. These variations are related to various socioeconomic, locational, density, and modal factors. A statistical framework consisting of the general linear model approach is used. This consists of a regression approach to analysis of variance designs. Both univariate and multivariate models are estimated to examine the variations in travel time, distance, and speed for the journey-to-work. The results consist of parameter estimates for each of the univariate models which are used for both hypothesis testing among factor levels and prediction; and graphs of the variation in the means of the different factor levels. Seven variables and associated two-way interactions are significant in explaining variation in the three travel measures. The absence of income as a significant explanatory variable or factor is a notable result.","abstract_html":"Variations in travel time, distance, and speed are identified for four Standard Metropolitan Statistical Areas. The unit of analysis consists of the journey-to-work for household heads. These variations are related to various socioeconomic, locational, density, and modal factors. A statistical framework consisting of the general linear model approach is used. This consists of a regression approach to analysis of variance designs. Both univariate and multivariate models are estimated to examine the variations in travel time, distance, and speed for the journey-to-work. The results consist of parameter estimates for each of the univariate models which are used for both hypothesis testing among factor levels and prediction; and graphs of the variation in the means of the different factor levels. Seven variables and associated two-way interactions are significant in explaining variation in the three travel measures. The absence of income as a significant explanatory variable or factor is a notable result.","abstract_has_math":false,"creators":["Ferris, Mark Edward"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-12-15T20:35:45Z","date_published":"2014-12-15T20:35:45Z","updated_at":"2026-07-22T22:26:01Z","subjects":["Engineering, Civil"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(UMI)AAI8218465"],"render_values":[{"text":"(UMI)AAI8218465","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/69904","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Ferris, Mark Edward"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2014-12-15T20:35:45Z","10000-01-01","1982"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil Engineering"]},{"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":["Engineering, Civil"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/69904","(UMI)AAI8218465"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Variations in travel time, distance, and speed are identified for four Standard Metropolitan Statistical Areas. The unit of analysis consists of the journey-to-work for household heads. These variations are related to various socioeconomic, locational, density, and modal factors. A statistical framework consisting of the general linear model approach is used. This consists of a regression approach to analysis of variance designs. Both univariate and multivariate models are estimated to examine the variations in travel time, distance, and speed for the journey-to-work. The results consist of parameter estimates for each of the univariate models which are used for both hypothesis testing among factor levels and prediction; and graphs of the variation in the means of the different factor levels. Seven variables and associated two-way interactions are significant in explaining variation in the three travel measures. The absence of income as a significant explanatory variable or factor is a notable result.","Made available in DSpace on 2014-12-15T20:35:45Z (GMT). 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These variations are related to various socioeconomic, locational, density, and modal factors. A statistical framework consisting of the general linear model approach is used. This consists of a regression approach to analysis of variance designs. Both univariate and multivariate models are estimated to examine the variations in travel time, distance, and speed for the journey-to-work. The results consist of parameter estimates for each of the univariate models which are used for both hypothesis testing among factor levels and prediction; and graphs of the variation in the means of the different factor levels. Seven variables and associated two-way interactions are significant in explaining variation in the three travel measures. The absence of income as a significant explanatory variable or factor is a notable result.","Made available in DSpace on 2014-12-15T20:35:45Z (GMT). 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