{"id":"https://openalex.org/W2944199214","doi":"https://doi.org/10.1080/03610918.2019.1610440","title":"Weighted composite quantile regression for longitudinal mixed effects models with application to AIDS studies","display_name":"Weighted composite quantile regression for longitudinal mixed effects models with application to AIDS studies","publication_year":2019,"publication_date":"2019-05-06","ids":{"openalex":"https://openalex.org/W2944199214","doi":"https://doi.org/10.1080/03610918.2019.1610440","mag":"2944199214"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2019.1610440","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1610440","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079518086","display_name":"Yuzhu Tian","orcid":"https://orcid.org/0000-0002-6173-0985"},"institutions":[{"id":"https://openalex.org/I68986083","display_name":"Northwest Normal University","ror":"https://ror.org/00gx3j908","country_code":"CN","type":"education","lineage":["https://openalex.org/I68986083"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuzhu Tian","raw_affiliation_strings":["School of Mathematics and Statistics, Northwest Normal University, Lanzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Northwest Normal University, Lanzhou, China","institution_ids":["https://openalex.org/I68986083"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051577475","display_name":"Liyong Wang","orcid":"https://orcid.org/0000-0002-0527-7063"},"institutions":[{"id":"https://openalex.org/I137867983","display_name":"Central University of Finance and Economics","ror":"https://ror.org/008e3hf02","country_code":"CN","type":"education","lineage":["https://openalex.org/I137867983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liyong Wang","raw_affiliation_strings":["School of Statistics and Mathematics, The Central University Of Finance and Economics, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Statistics and Mathematics, The Central University Of Finance and Economics, Beijing, China","institution_ids":["https://openalex.org/I137867983"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069557245","display_name":"Man\u2010Lai Tang","orcid":"https://orcid.org/0000-0001-6460-8136"},"institutions":[{"id":"https://openalex.org/I47605537","display_name":"The Hang Seng University of Hong Kong","ror":"https://ror.org/04fa64g55","country_code":"CN","type":"education","lineage":["https://openalex.org/I47605537"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Manlai Tang","raw_affiliation_strings":["Department of Mathematics and Statistics, The HangSeng University of Hong Kong, Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, The HangSeng University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I47605537","https://openalex.org/I889458895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081970358","display_name":"Maozai Tian","orcid":"https://orcid.org/0000-0002-0515-4477"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Maozai Tian","raw_affiliation_strings":["School of Statistics, Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Statistics, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5079518086"],"corresponding_institution_ids":["https://openalex.org/I68986083"],"apc_list":null,"apc_paid":null,"fwci":0.7024,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.71222045,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"50","issue":"6","first_page":"1837","last_page":"1853"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5877626538276672},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5404970645904541},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5247278809547424},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.49549853801727295},{"id":"https://openalex.org/keywords/quantile-regression","display_name":"Quantile regression","score":0.4938236176967621},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.48642683029174805},{"id":"https://openalex.org/keywords/quantile","display_name":"Quantile","score":0.4670732319355011},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.348184198141098}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5877626538276672},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5404970645904541},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5247278809547424},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.49549853801727295},{"id":"https://openalex.org/C63817138","wikidata":"https://www.wikidata.org/wiki/Q3455889","display_name":"Quantile regression","level":2,"score":0.4938236176967621},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.48642683029174805},{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.4670732319355011},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.348184198141098}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2019.1610440","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1610440","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.699999988079071,"id":"https://metadata.un.org/sdg/3"}],"awards":[{"id":"https://openalex.org/G5122393514","display_name":null,"funder_award_id":"2017M610156","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G6678007391","display_name":null,"funder_award_id":"11501167","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W41409100","https://openalex.org/W381804301","https://openalex.org/W656838156","https://openalex.org/W1920881695","https://openalex.org/W1981090284","https://openalex.org/W1981463702","https://openalex.org/W1996742192","https://openalex.org/W1998073888","https://openalex.org/W2006080807","https://openalex.org/W2019165610","https://openalex.org/W2024510798","https://openalex.org/W2024544539","https://openalex.org/W2035673851","https://openalex.org/W2037591816","https://openalex.org/W2041580290","https://openalex.org/W2060275668","https://openalex.org/W2062380248","https://openalex.org/W2076881231","https://openalex.org/W2078722674","https://openalex.org/W2082246284","https://openalex.org/W2084007633","https://openalex.org/W2084871407","https://openalex.org/W2090692107","https://openalex.org/W2096904991","https://openalex.org/W2097168082","https://openalex.org/W2117978909","https://openalex.org/W2119608836","https://openalex.org/W2121956497","https://openalex.org/W2138198368","https://openalex.org/W2149436507","https://openalex.org/W2161896685","https://openalex.org/W2346148797","https://openalex.org/W2410962349","https://openalex.org/W2460737317","https://openalex.org/W2498354217","https://openalex.org/W2560347591","https://openalex.org/W2802876434","https://openalex.org/W2912397373","https://openalex.org/W3099697354","https://openalex.org/W4241653265","https://openalex.org/W4255619213","https://openalex.org/W4388319941"],"related_works":["https://openalex.org/W2963308895","https://openalex.org/W4206511378","https://openalex.org/W4298801152","https://openalex.org/W4206618949","https://openalex.org/W2185047231","https://openalex.org/W1966919947","https://openalex.org/W2588275121","https://openalex.org/W2526321210","https://openalex.org/W2999188005","https://openalex.org/W2159903438"],"abstract_inverted_index":{"In":[0,67],"longitudinal":[1,76],"data":[2,143],"studies,":[3],"a":[4,72,80],"conjunct":[5],"feature":[6],"of":[7,18,30,61,75,95,104,115],"the":[8,15,22,27,62,85,92,96,100,105,109,119,127],"multitudinous":[9],"statistical":[10],"methods":[11],"is":[12,25],"to":[13],"depict":[14],"conditional":[16,23],"mean":[17,24],"outcome":[19],"variable.":[20],"However,":[21],"not":[26],"best":[28],"measure":[29],"centrality":[31],"which":[32],"may":[33],"be":[34],"affected":[35],"by":[36,132],"outliers.":[37],"As":[38],"an":[39,137],"available":[40],"alterative,":[41],"composite":[42,86],"quantile":[43],"regression":[44,58],"(CQR)":[45],"can":[46],"result":[47],"in":[48,57],"robust":[49],"estimation":[50,65],"results":[51],"even":[52],"for":[53],"non-normal":[54],"error":[55],"distributions":[56],"analysis":[59],"instead":[60],"least":[63,112],"square":[64,113],"(LSE).":[66],"this":[68],"paper,":[69],"we":[70,98],"develop":[71],"weighted":[73,111],"CQR":[74],"mixed":[77],"model":[78,106],"from":[79],"likelihood":[81,103],"framework":[82],"based":[83],"on":[84],"asymmetric":[87],"Laplace":[88],"distribution":[89],"(CALD).":[90],"Using":[91],"mixture":[93],"representation":[94],"CALD,":[97],"establish":[99],"joint":[101],"hierarchical":[102],"and":[107,136],"achieve":[108],"iterative":[110],"estimators":[114],"unknown":[116],"parameters":[117],"via":[118],"MCEM":[120],"(Monte":[121],"Carlo":[122,134],"Expectation":[123],"Maximization)":[124],"algorithm.":[125],"Finally,":[126],"developed":[128],"procedures":[129],"are":[130],"illustrated":[131],"Monte":[133],"simulations":[135],"AIDS":[138],"(Acquired":[139],"Immune":[140],"Deficiency":[141],"Syndrome)":[142],"analysis.":[144]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2026-02-25T23:00:34.991745","created_date":"2025-10-10T00:00:00"}