{"id":"https://openalex.org/W3163761441","doi":"https://doi.org/10.1080/03610918.2021.1926499","title":"Bi-level variable selection in semiparametric transformation mixture cure models for right-censored data","display_name":"Bi-level variable selection in semiparametric transformation mixture cure models for right-censored data","publication_year":2021,"publication_date":"2021-05-17","ids":{"openalex":"https://openalex.org/W3163761441","doi":"https://doi.org/10.1080/03610918.2021.1926499","mag":"3163761441"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2021.1926499","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2021.1926499","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/A5088751017","display_name":"Jingjing Wu","orcid":"https://orcid.org/0000-0003-4555-1490"},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"education","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Jingjing Wu","raw_affiliation_strings":["Department of Mathematics and Statistics, University of Calgary, Calgary, Alberta, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, University of Calgary, Calgary, Alberta, Canada","institution_ids":["https://openalex.org/I168635309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065562860","display_name":"Xuewen Lu","orcid":"https://orcid.org/0000-0002-0905-2697"},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"education","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Xuewen Lu","raw_affiliation_strings":["Department of Mathematics and Statistics, University of Calgary, Calgary, Alberta, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, University of Calgary, Calgary, Alberta, Canada","institution_ids":["https://openalex.org/I168635309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038089319","display_name":"Wenyan Zhong","orcid":null},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"education","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Wenyan Zhong","raw_affiliation_strings":["Department of Biostatistics and Research Decision Sciences, MSD China, Shanghai, China","Department of Mathematics and Statistics, University of Calgary, Calgary, Alberta, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Biostatistics and Research Decision Sciences, MSD China, Shanghai, China","institution_ids":[]},{"raw_affiliation_string":"Department of Mathematics and Statistics, University of Calgary, Calgary, Alberta, Canada","institution_ids":["https://openalex.org/I168635309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5088751017"],"corresponding_institution_ids":["https://openalex.org/I168635309"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07446756,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"52","issue":"7","first_page":"3006","last_page":"3025"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.998199999332428,"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":0.998199999332428,"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":0.9961000084877014,"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":0.9751999974250793,"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/semiparametric-model","display_name":"Semiparametric model","score":0.6863172650337219},{"id":"https://openalex.org/keywords/semiparametric-regression","display_name":"Semiparametric regression","score":0.6747597455978394},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.576668381690979},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.5665806531906128},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5546108484268188},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.5383466482162476},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.508449912071228},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4992713928222656},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.479289710521698},{"id":"https://openalex.org/keywords/survival-function","display_name":"Survival function","score":0.47247692942619324},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.4664947986602783},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.45617175102233887},{"id":"https://openalex.org/keywords/accelerated-failure-time-model","display_name":"Accelerated failure time model","score":0.4290756285190582},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.32735830545425415},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.29852813482284546},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.29561758041381836},{"id":"https://openalex.org/keywords/survival-analysis","display_name":"Survival analysis","score":0.25966280698776245},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.19769331812858582},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.15833374857902527},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.06738471984863281}],"concepts":[{"id":"https://openalex.org/C78297888","wikidata":"https://www.wikidata.org/wiki/Q7449607","display_name":"Semiparametric model","level":3,"score":0.6863172650337219},{"id":"https://openalex.org/C19539793","wikidata":"https://www.wikidata.org/wiki/Q7449609","display_name":"Semiparametric regression","level":3,"score":0.6747597455978394},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.576668381690979},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.5665806531906128},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5546108484268188},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5383466482162476},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.508449912071228},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4992713928222656},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.479289710521698},{"id":"https://openalex.org/C42600057","wikidata":"https://www.wikidata.org/wiki/Q2915096","display_name":"Survival function","level":3,"score":0.47247692942619324},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.4664947986602783},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.45617175102233887},{"id":"https://openalex.org/C33114746","wikidata":"https://www.wikidata.org/wiki/Q4672282","display_name":"Accelerated failure time model","level":3,"score":0.4290756285190582},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.32735830545425415},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.29852813482284546},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.29561758041381836},{"id":"https://openalex.org/C10515644","wikidata":"https://www.wikidata.org/wiki/Q543310","display_name":"Survival analysis","level":2,"score":0.25966280698776245},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19769331812858582},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.15833374857902527},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.06738471984863281},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2021.1926499","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2021.1926499","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":[{"score":0.6399999856948853,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1589848011","https://openalex.org/W1931583310","https://openalex.org/W1966787736","https://openalex.org/W1967579825","https://openalex.org/W1969094789","https://openalex.org/W1984130041","https://openalex.org/W1994309289","https://openalex.org/W2007022861","https://openalex.org/W2014360396","https://openalex.org/W2033585005","https://openalex.org/W2051305724","https://openalex.org/W2054596996","https://openalex.org/W2078574341","https://openalex.org/W2086924664","https://openalex.org/W2108715089","https://openalex.org/W2120160881","https://openalex.org/W2135046866","https://openalex.org/W2138019504","https://openalex.org/W2141789862","https://openalex.org/W2153045803","https://openalex.org/W2166379450","https://openalex.org/W2170987805","https://openalex.org/W2315373884","https://openalex.org/W3099503819"],"related_works":["https://openalex.org/W3123217622","https://openalex.org/W3151010055","https://openalex.org/W1532780914","https://openalex.org/W3122686941","https://openalex.org/W2393877243","https://openalex.org/W2090382595","https://openalex.org/W2046181616","https://openalex.org/W3139122440","https://openalex.org/W2889804998","https://openalex.org/W2082883684"],"abstract_inverted_index":{"We":[0],"investigate":[1],"the":[2,30,39,61,75,80,88,92,96],"bi-level":[3,54],"variable":[4,45,55],"selection":[5,56],"problem":[6],"in":[7],"semiparametric":[8,26],"transformation":[9,27],"mixture":[10,18,62],"cure":[11,19,63,89],"models":[12,28],"(STMCM).":[13],"In":[14],"this":[15],"type":[16],"of":[17,25,60],"models,":[20],"we":[21,72],"consider":[22],"a":[23,35],"class":[24],"for":[29,38,53,95],"conditional":[31],"survival":[32,93],"function":[33,94],"and":[34,68,83,91],"logistic":[36],"regression":[37],"incidence":[40],"component,":[41],"then":[42],"conduct":[43],"group":[44,48],"selection.":[46],"The":[47],"bridge":[49],"penalty":[50],"is":[51],"adopted":[52],"on":[57],"both":[58],"parts":[59],"models.":[64],"Through":[65],"simulation":[66],"studies":[67],"real":[69],"data":[70],"analyses,":[71],"show":[73],"that":[74,85],"proposed":[76],"method":[77],"can":[78],"identify":[79],"important":[81],"variables":[82],"groups":[84],"contribute":[86],"to":[87],"proportion":[90],"uncured":[97],"subjects,":[98],"respectively.":[99]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
