{"id":"https://openalex.org/W2922309978","doi":"https://doi.org/10.1080/03610918.2019.1571605","title":"Variable selection with group LASSO approach: Application to Cox regression with frailty model","display_name":"Variable selection with group LASSO approach: Application to Cox regression with frailty model","publication_year":2019,"publication_date":"2019-03-11","ids":{"openalex":"https://openalex.org/W2922309978","doi":"https://doi.org/10.1080/03610918.2019.1571605","mag":"2922309978","pmid":"https://pubmed.ncbi.nlm.nih.gov/34248255"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2019.1571605","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1571605","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","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8261624","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005298452","display_name":"Jean Claude Utazirubanda","orcid":"https://orcid.org/0000-0003-2907-1833"},"institutions":[{"id":"https://openalex.org/I96840727","display_name":"Cheikh Anta Diop University","ror":"https://ror.org/04je6yw13","country_code":"SN","type":"education","lineage":["https://openalex.org/I96840727"]}],"countries":["SN"],"is_corresponding":false,"raw_author_name":"Jean Claude Utazirubanda","raw_affiliation_strings":["LMA, Universit\u00e9 Cheikh Anta Diop, Dakar, Senegal"],"raw_orcid":"https://orcid.org/0000-0003-2907-1833","affiliations":[{"raw_affiliation_string":"LMA, Universit\u00e9 Cheikh Anta Diop, Dakar, Senegal","institution_ids":["https://openalex.org/I96840727"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029718103","display_name":"Tom\u00e1s M. Le\u00f3n","orcid":"https://orcid.org/0000-0002-7633-677X"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tom\u00e1s M. Le\u00f3n","raw_affiliation_strings":["School of Public Health, University of California, Berkeley, California, USA"],"raw_orcid":"https://orcid.org/0000-0002-7633-677X","affiliations":[{"raw_affiliation_string":"School of Public Health, University of California, Berkeley, California, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088241054","display_name":"Papa Ngom","orcid":"https://orcid.org/0000-0002-6525-017X"},"institutions":[{"id":"https://openalex.org/I96840727","display_name":"Cheikh Anta Diop University","ror":"https://ror.org/04je6yw13","country_code":"SN","type":"education","lineage":["https://openalex.org/I96840727"]}],"countries":["SN"],"is_corresponding":true,"raw_author_name":"Papa Ngom","raw_affiliation_strings":["LMA, Universit\u00e9 Cheikh Anta Diop, Dakar, Senegal"],"raw_orcid":"https://orcid.org/0000-0002-6525-017X","affiliations":[{"raw_affiliation_string":"LMA, Universit\u00e9 Cheikh Anta Diop, Dakar, Senegal","institution_ids":["https://openalex.org/I96840727"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5029718103","https://openalex.org/A5088241054"],"corresponding_institution_ids":["https://openalex.org/I95457486","https://openalex.org/I96840727"],"apc_list":null,"apc_paid":null,"fwci":1.8762,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.8696243,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"50","issue":"3","first_page":"881","last_page":"901"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9962000250816345,"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":0.9962000250816345,"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/T10845","display_name":"Advanced Causal Inference Techniques","score":0.972000002861023,"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/T10190","display_name":"Air Quality and Health Impacts","score":0.9474999904632568,"subfield":{"id":"https://openalex.org/subfields/2307","display_name":"Health, Toxicology and Mutagenesis"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.8498659133911133},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.7903841733932495},{"id":"https://openalex.org/keywords/proportional-hazards-model","display_name":"Proportional hazards model","score":0.6640251874923706},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.57278972864151},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5576561689376831},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5573131442070007},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.5255148410797119},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5245466828346252},{"id":"https://openalex.org/keywords/group-selection","display_name":"Group selection","score":0.509757936000824},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.4616512060165405},{"id":"https://openalex.org/keywords/accelerated-failure-time-model","display_name":"Accelerated failure time model","score":0.4175627827644348},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.41726359724998474},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.3864386975765228},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.33835482597351074},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3351151645183563},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23586693406105042},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22086209058761597},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21726858615875244}],"concepts":[{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.8498659133911133},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.7903841733932495},{"id":"https://openalex.org/C50382708","wikidata":"https://www.wikidata.org/wiki/Q223218","display_name":"Proportional hazards model","level":2,"score":0.6640251874923706},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.57278972864151},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5576561689376831},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5573131442070007},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.5255148410797119},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5245466828346252},{"id":"https://openalex.org/C51520907","wikidata":"https://www.wikidata.org/wiki/Q874437","display_name":"Group selection","level":3,"score":0.509757936000824},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4616512060165405},{"id":"https://openalex.org/C33114746","wikidata":"https://www.wikidata.org/wiki/Q4672282","display_name":"Accelerated failure time model","level":3,"score":0.4175627827644348},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.41726359724998474},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3864386975765228},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.33835482597351074},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3351151645183563},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23586693406105042},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22086209058761597},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21726858615875244},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1080/03610918.2019.1571605","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1571605","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"},{"id":"pmid:34248255","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34248255","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in statistics: Simulation and computation","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:8261624","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8261624","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Commun Stat Simul Comput","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:8261624","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8261624","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Commun Stat Simul Comput","raw_type":"Text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.4399999976158142,"display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G2722875964","display_name":null,"funder_award_id":"U54 GM111274","funder_id":"https://openalex.org/F4320337354","funder_display_name":"National Institute of General Medical Sciences"},{"id":"https://openalex.org/G8843488058","display_name":null,"funder_award_id":"U54GM111274","funder_id":"https://openalex.org/F4320337354","funder_display_name":"National Institute of General Medical Sciences"}],"funders":[{"id":"https://openalex.org/F4320337354","display_name":"National Institute of General Medical Sciences","ror":"https://ror.org/04q48ey07"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W137628093","https://openalex.org/W1460189015","https://openalex.org/W1489433677","https://openalex.org/W1580788756","https://openalex.org/W1931583310","https://openalex.org/W1972163814","https://openalex.org/W1976564639","https://openalex.org/W1978358551","https://openalex.org/W1986705681","https://openalex.org/W1997413230","https://openalex.org/W2003942385","https://openalex.org/W2020925091","https://openalex.org/W2037796411","https://openalex.org/W2046172123","https://openalex.org/W2047529648","https://openalex.org/W2056124784","https://openalex.org/W2057516887","https://openalex.org/W2058815839","https://openalex.org/W2074682976","https://openalex.org/W2106161928","https://openalex.org/W2106393550","https://openalex.org/W2106398669","https://openalex.org/W2124831990","https://openalex.org/W2135046866","https://openalex.org/W2138019504","https://openalex.org/W2141613549","https://openalex.org/W2144278613","https://openalex.org/W2145473366","https://openalex.org/W2149199519","https://openalex.org/W2166183437","https://openalex.org/W2168175751","https://openalex.org/W2172003817","https://openalex.org/W2536368354","https://openalex.org/W2614237344","https://openalex.org/W2740865402","https://openalex.org/W2765388298","https://openalex.org/W2797482815","https://openalex.org/W2963034386","https://openalex.org/W3000332379","https://openalex.org/W3020570927","https://openalex.org/W3135856140","https://openalex.org/W4234698323","https://openalex.org/W4238943743","https://openalex.org/W4256170606"],"related_works":["https://openalex.org/W128985311","https://openalex.org/W2800721711","https://openalex.org/W4241791143","https://openalex.org/W2400325187","https://openalex.org/W2990428857","https://openalex.org/W2778586139","https://openalex.org/W2901626990","https://openalex.org/W4390798516","https://openalex.org/W2380754093","https://openalex.org/W1973887383"],"abstract_inverted_index":{"In":[0,98],"analysis":[1,161],"of":[2,16,35,85,133,148,185],"survival":[3],"outcomes":[4],"supplemented":[5],"with":[6,105,169,187],"both":[7],"clinical":[8],"information":[9],"and":[10,59,128,157,175,191],"high-dimensional":[11],"gene":[12,51],"expression":[13,52],"data,":[14],"use":[15,184],"the":[17,33,41,69,82,134,183],"traditional":[18],"Cox":[19,70,112],"proportional":[20],"hazards":[21],"model":[22,71],"fails":[23],"to":[24,92,118,126,153],"meet":[25],"some":[26],"emerging":[27],"needs":[28],"in":[29,111],"biomedical":[30],"research.":[31],"First,":[32],"number":[34],"covariates":[36],"is":[37,53,67,88,137,141],"generally":[38],"much":[39],"larger":[40],"sample":[42],"size.":[43],"Secondly,":[44],"predicting":[45],"an":[46],"outcome":[47],"based":[48],"on":[49],"individual":[50],"inadequate":[54],"because":[55],"multiple":[56],"biological":[57],"processes":[58],"functional":[60],"pathways":[61],"regulate":[62],"phenotypic":[63],"expression.":[64],"Another":[65],"challenge":[66],"that":[68,73,78],"assumes":[72],"populations":[74],"are":[75],"homogenous,":[76],"implying":[77],"all":[79],"individuals":[80],"have":[81],"same":[83],"risk":[84,94],"death,":[86],"which":[87],"rarely":[89],"true":[90],"due":[91],"unmeasured":[93],"factors":[95],"among":[96,122],"populations.":[97],"this":[99],"paper":[100],"we":[101],"propose":[102],"group":[103,123,166,173,176,189,193],"LASSO":[104,167,190,194],"gamma-distributed":[106],"frailty":[107,186],"for":[108,120,143],"variable":[109],"selection":[110],"regression":[113],"by":[114,165],"extending":[115],"previous":[116],"scholarship":[117],"account":[119],"heterogeneity":[121],"structures":[124],"related":[125],"exposure":[127],"susceptibility.":[129],"The":[130],"consistency":[131],"property":[132],"proposed":[135],"method":[136,140],"established.":[138],"This":[139],"appropriate":[142],"addressing":[144],"a":[145],"wide":[146],"variety":[147],"research":[149,179],"questions":[150],"from":[151],"genetics":[152],"air":[154],"pollution.":[155],"Simulated":[156],"real":[158],"world":[159],"data":[160],"shows":[162],"promising":[163],"performance":[164],"compared":[168],"other":[170],"methods,":[171],"including":[172],"SCAD":[174],"MCP.":[177],"Future":[178],"directions":[180],"include":[181],"expanding":[182],"adaptive":[188],"sparse":[192],"methods.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}