{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/87408"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/87408","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Inference on Quantile Regression for Mixed Models With Applications to GeneChip Data","abstract":"The proposed test is motivated by studies of GeneChip data to identify differentially expressed genes through the analysis of probe level measurements. Realizing that the number of replicates is usually small in GeneChip studies, we propose a genome-wide adjustment to the test statistic to account for within-array correlation and several enhanced quantile approaches by borrowing information across genes. Our empirical studies of GeneChip data show that inference on the quartiles of the gene expression distribution is a valuable complement to the usual mixed model analysis based on Gaussian likelihood.","abstract_html":"The proposed test is motivated by studies of GeneChip data to identify differentially expressed genes through the analysis of probe level measurements. Realizing that the number of replicates is usually small in GeneChip studies, we propose a genome-wide adjustment to the test statistic to account for within-array correlation and several enhanced quantile approaches by borrowing information across genes. Our empirical studies of GeneChip data show that inference on the quartiles of the gene expression distribution is a valuable complement to the usual mixed model analysis based on Gaussian likelihood.","abstract_has_math":false,"creators":["Wang, Huixia"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Statistics","degree_department":null,"school":null,"contributors":["He, Xuming"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-28T16:02:44Z","date_published":"2015-09-28T16:02:44Z","updated_at":"2026-07-22T22:26:30Z","subjects":["Statistics"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI3243019"],"render_values":[{"text":"(MiAaPQ)AAI3243019","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/87408","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["He, Xuming"]},{"key":"dc:creator","label":"Author","values":["Wang, Huixia"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-28T16:02:44Z","10000-01-01","2006"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Statistics"]},{"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":["Statistics"]}]},{"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/2142/87408","(MiAaPQ)AAI3243019"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The proposed test is motivated by studies of GeneChip data to identify differentially expressed genes through the analysis of probe level measurements. Realizing that the number of replicates is usually small in GeneChip studies, we propose a genome-wide adjustment to the test statistic to account for within-array correlation and several enhanced quantile approaches by borrowing information across genes. Our empirical studies of GeneChip data show that inference on the quartiles of the gene expression distribution is a valuable complement to the usual mixed model analysis based on Gaussian likelihood.","Made available in DSpace on 2015-09-28T16:02:44Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3243019.pdf: 2895039 bytes, checksum: 1fb84b386b865a4f428ad91693f3199d (MD5) Previous issue date: 2006","Embargo set by: Seth Robbins for item 88689 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","U of I Only","114 p.","Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006."]},{"key":"dc:title","label":"Title","values":["Inference on Quantile Regression for Mixed Models With Applications to GeneChip Data"]}]}],"canonical_facts":{"dc:contributor":["He, Xuming"],"dc:creator":["Wang, Huixia"],"dc:date":["2015-09-28T16:02:44Z","10000-01-01","2006"],"dc:description":["The proposed test is motivated by studies of GeneChip data to identify differentially expressed genes through the analysis of probe level measurements. Realizing that the number of replicates is usually small in GeneChip studies, we propose a genome-wide adjustment to the test statistic to account for within-array correlation and several enhanced quantile approaches by borrowing information across genes. Our empirical studies of GeneChip data show that inference on the quartiles of the gene expression distribution is a valuable complement to the usual mixed model analysis based on Gaussian likelihood.","Made available in DSpace on 2015-09-28T16:02:44Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3243019.pdf: 2895039 bytes, checksum: 1fb84b386b865a4f428ad91693f3199d (MD5) Previous issue date: 2006","Embargo set by: Seth Robbins for item 88689 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","U of I Only","114 p.","Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006."],"dc:identifier":["http://hdl.handle.net/2142/87408","(MiAaPQ)AAI3243019"],"dc:language":["eng"],"dc:subject":["Statistics"],"dc:title":["Inference on Quantile Regression for Mixed Models With Applications to GeneChip Data"],"dc:type":["text"],"thesis:degree_discipline":["Statistics"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:26:30Z"}