{"id":"https://openalex.org/W4206915945","doi":"https://doi.org/10.1080/10618600.2022.2032723","title":"A Generalized Quantile Tree Method for Subgroup Identification","display_name":"A Generalized Quantile Tree Method for Subgroup Identification","publication_year":2022,"publication_date":"2022-01-24","ids":{"openalex":"https://openalex.org/W4206915945","doi":"https://doi.org/10.1080/10618600.2022.2032723"},"language":"en","primary_location":{"id":"doi:10.1080/10618600.2022.2032723","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2022.2032723","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"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":"Journal of Computational and Graphical Statistics","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/A5005522695","display_name":"Xiang Peng","orcid":"https://orcid.org/0000-0003-3453-4062"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiang Peng","raw_affiliation_strings":["Department of Statistics, George Washington University, Washington, DC;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, George Washington University, Washington, DC;","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018732669","display_name":"Huixia Wang","orcid":"https://orcid.org/0000-0002-5195-8564"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Huixia Judy Wang","raw_affiliation_strings":["Department of Statistics, George Washington University, Washington, DC;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, George Washington University, Washington, DC;","institution_ids":["https://openalex.org/I193531525"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5018732669"],"corresponding_institution_ids":["https://openalex.org/I193531525"],"apc_list":null,"apc_paid":null,"fwci":0.4656,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.61293351,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"31","issue":"3","first_page":"824","last_page":"834"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9958000183105469,"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/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9958000183105469,"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/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.995199978351593,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9886000156402588,"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/quantile","display_name":"Quantile","score":0.6924870014190674},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6081950664520264},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5201737880706787},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5173389315605164},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4586508274078369},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3931238055229187},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3317645192146301},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.20823723077774048}],"concepts":[{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.6924870014190674},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6081950664520264},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5201737880706787},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5173389315605164},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4586508274078369},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3931238055229187},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3317645192146301},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.20823723077774048},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/10618600.2022.2032723","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2022.2032723","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"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":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.6899999976158142,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1689333044","https://openalex.org/W1919599643","https://openalex.org/W1974022463","https://openalex.org/W1988004867","https://openalex.org/W1992015234","https://openalex.org/W1992363678","https://openalex.org/W1994149193","https://openalex.org/W1996742192","https://openalex.org/W2000239378","https://openalex.org/W2003336670","https://openalex.org/W2035583871","https://openalex.org/W2036197503","https://openalex.org/W2039414656","https://openalex.org/W2045803758","https://openalex.org/W2046628605","https://openalex.org/W2052829936","https://openalex.org/W2058248640","https://openalex.org/W2064097590","https://openalex.org/W2065532917","https://openalex.org/W2073464636","https://openalex.org/W2100974168","https://openalex.org/W2106298710","https://openalex.org/W2108143085","https://openalex.org/W2111980395","https://openalex.org/W2118704147","https://openalex.org/W2118711140","https://openalex.org/W2121819178","https://openalex.org/W2130939988","https://openalex.org/W2150531984","https://openalex.org/W2153646525","https://openalex.org/W2164481774","https://openalex.org/W2330820318","https://openalex.org/W2336765814","https://openalex.org/W2396610607","https://openalex.org/W2471100994","https://openalex.org/W2520742786","https://openalex.org/W2585846175","https://openalex.org/W2782237628","https://openalex.org/W3010019900","https://openalex.org/W3099697354","https://openalex.org/W3100189218","https://openalex.org/W3105435006","https://openalex.org/W3105706340"],"related_works":["https://openalex.org/W2581236533","https://openalex.org/W2525669318","https://openalex.org/W2052558588","https://openalex.org/W3121392242","https://openalex.org/W3183286748","https://openalex.org/W2059186684","https://openalex.org/W2114668360","https://openalex.org/W4301311151","https://openalex.org/W4200167157","https://openalex.org/W3135104130"],"abstract_inverted_index":{"One":[0],"primary":[1],"goal":[2],"of":[3,10,84,114,141,149],"subgroup":[4,52,126],"analysis":[5,148],"is":[6,82,144],"to":[7,62],"identify":[8],"subgroups":[9],"subjects":[11],"with":[12,133],"differential":[13],"treatment":[14,23,102],"effects.":[15],"Existing":[16],"methods":[17,130],"have":[18],"focused":[19],"on":[20],"the":[21,30,38,69,110,120,142,147],"mean":[22],"effect":[24,103],"and":[25,66,88,92,105,112],"may":[26],"be":[27],"ineffective":[28],"when":[29],"two":[31],"distributions":[32],"differ":[33],"in":[34,37],"scales":[35],"or":[36,40,135],"upper":[39],"lower":[41],"tails.":[42],"We":[43],"develop":[44],"a":[45,74,99,106],"new":[46],"generalized":[47,100],"quantile":[48,58,76,101],"tree":[49],"method":[50,55,108,122,143],"for":[51,109,131,157],"identification.":[53],"The":[54,78,138],"first":[56],"uses":[57],"rank":[59],"score":[60],"tests":[61],"select":[63],"split":[64,70,80],"variables":[65],"then":[67],"estimates":[68],"point":[71],"by":[72],"minimizing":[73],"composite":[75],"loss.":[77],"proposed":[79,121],"rule":[81],"free":[83],"variable":[85],"selection":[86,111],"bias":[87],"robust":[89],"against":[90],"outliers":[91],"heavy-tailed":[93,136],"distributions.":[94],"In":[95],"addition,":[96],"we":[97],"introduce":[98],"estimator":[104],"testing":[107],"confirmation":[113],"predictive":[115],"subgroups.":[116],"Simulation":[117],"shows":[118],"that":[119],"gives":[123],"more":[124],"accurate":[125],"identification":[127],"than":[128],"existing":[129],"cases":[132],"heteroscedastic":[134],"errors.":[137],"practical":[139],"value":[140],"demonstrated":[145],"through":[146],"an":[150],"AIDS":[151],"clinical":[152],"trial":[153],"data.":[154],"Supplementary":[155],"materials":[156],"this":[158],"article":[159],"are":[160],"available":[161],"online.":[162]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}