{"id":"https://openalex.org/W4285389421","doi":"https://doi.org/10.1080/03610918.2022.2098332","title":"Penalized regression analysis with individual-specific patterns of missing covariates","display_name":"Penalized regression analysis with individual-specific patterns of missing covariates","publication_year":2022,"publication_date":"2022-07-14","ids":{"openalex":"https://openalex.org/W4285389421","doi":"https://doi.org/10.1080/03610918.2022.2098332"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2022.2098332","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2098332","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/A5080234910","display_name":"Zhishuai Liu","orcid":null},"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":"Zhishuai Liu","raw_affiliation_strings":["Center for Applied Statistics, Renmin University of China","Center for Applied Statistics, Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Center for Applied Statistics, Renmin University of China","institution_ids":["https://openalex.org/I78988378"]},{"raw_affiliation_string":"Center for Applied Statistics, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063425025","display_name":"Zishu Zhan","orcid":null},"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":"Zishu Zhan","raw_affiliation_strings":["Center for Applied Statistics, Renmin University of China","Center for Applied Statistics, Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Center for Applied Statistics, Renmin University of China","institution_ids":["https://openalex.org/I78988378"]},{"raw_affiliation_string":"Center for Applied Statistics, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043395097","display_name":"Cunjie Lin","orcid":"https://orcid.org/0000-0001-5043-0680"},"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":true,"raw_author_name":"Cunjie Lin","raw_affiliation_strings":["Center for Applied Statistics, Renmin University of China","School of Statistics, Renmin University of China","School of Statistics, Renmin University of China, Beijing, China","Center for Applied Statistics, Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Center for Applied Statistics, Renmin University of China","institution_ids":["https://openalex.org/I78988378"]},{"raw_affiliation_string":"School of Statistics, Renmin University of China","institution_ids":["https://openalex.org/I78988378"]},{"raw_affiliation_string":"School of Statistics, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]},{"raw_affiliation_string":"Center for Applied Statistics, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5043395097"],"corresponding_institution_ids":["https://openalex.org/I78988378"],"apc_list":null,"apc_paid":null,"fwci":0.4863,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.65298668,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"53","issue":"7","first_page":"3126","last_page":"3142"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9983000159263611,"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":0.9983000159263611,"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":0.9962999820709229,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9958999752998352,"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/missing-data","display_name":"Missing data","score":0.9475349187850952},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.821329653263092},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.8055960536003113},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6101590394973755},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5579473972320557},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5346241593360901},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.47875848412513733},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4647338390350342},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.45986437797546387},{"id":"https://openalex.org/keywords/partial-least-squares-regression","display_name":"Partial least squares regression","score":0.4229537844657898},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3782542943954468},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31021302938461304},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2574262320995331},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.24970698356628418}],"concepts":[{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.9475349187850952},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.821329653263092},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.8055960536003113},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6101590394973755},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5579473972320557},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5346241593360901},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.47875848412513733},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4647338390350342},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.45986437797546387},{"id":"https://openalex.org/C22354355","wikidata":"https://www.wikidata.org/wiki/Q422009","display_name":"Partial least squares regression","level":2,"score":0.4229537844657898},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3782542943954468},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31021302938461304},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2574262320995331},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.24970698356628418}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2022.2098332","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2098332","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W105168457","https://openalex.org/W105319308","https://openalex.org/W612972800","https://openalex.org/W1968694834","https://openalex.org/W1986705681","https://openalex.org/W2006021405","https://openalex.org/W2015374677","https://openalex.org/W2021746604","https://openalex.org/W2027123933","https://openalex.org/W2046124401","https://openalex.org/W2074682976","https://openalex.org/W2075651107","https://openalex.org/W2088945244","https://openalex.org/W2101083207","https://openalex.org/W2109553965","https://openalex.org/W2130102576","https://openalex.org/W2135046866","https://openalex.org/W2149752470","https://openalex.org/W2167031636","https://openalex.org/W2169103656","https://openalex.org/W2315490857","https://openalex.org/W2480680997","https://openalex.org/W2562162676","https://openalex.org/W2954765588","https://openalex.org/W3023714059","https://openalex.org/W3037000643","https://openalex.org/W3123972126","https://openalex.org/W4398284234","https://openalex.org/W6608704830"],"related_works":["https://openalex.org/W2181530120","https://openalex.org/W4211215373","https://openalex.org/W2024529227","https://openalex.org/W1574575415","https://openalex.org/W3144172081","https://openalex.org/W3179858851","https://openalex.org/W3028371478","https://openalex.org/W2081476516","https://openalex.org/W3032945164","https://openalex.org/W2057612738"],"abstract_inverted_index":{"High-dimensional":[0],"but":[1],"incomplete":[2],"data":[3,21,52,104],"are":[4,76],"common":[5],"in":[6],"many":[7],"settings.":[8],"With":[9],"such":[10],"data,":[11],"regularized":[12],"estimation":[13,42],"and":[14,57,71,79],"variable":[15,72],"selection":[16],"techniques":[17,50],"developed":[18],"for":[19,51],"complete":[20],"fail":[22],"to":[23,28],"produce":[24],"reliable":[25],"results":[26],"due":[27],"the":[29,107,110],"missingness.":[30],"To":[31],"address":[32],"this":[33],"problem,":[34],"we":[35],"propose":[36],"an":[37],"iterative":[38],"penalized":[39,48],"least":[40],"squares":[41],"(IPLSE)":[43],"method,":[44],"which":[45],"customizes":[46],"existing":[47],"regression":[49],"with":[53],"high":[54],"missing":[55,59,66,88],"rates":[56],"individual-specific":[58],"patterns.":[60],"The":[61],"proposed":[62,111],"method":[63],"simultaneously":[64],"conducts":[65],"value":[67],"imputation,":[68],"parameter":[69],"estimation,":[70],"selection.":[73],"Statistical":[74],"properties":[75],"rigorously":[77],"established,":[78],"a":[80],"simulation":[81],"demonstrates":[82],"its":[83],"competitive":[84],"performance":[85],"under":[86],"various":[87],"patterns,":[89],"especially":[90],"when":[91],"there":[92],"is":[93],"missingness":[94],"concerning":[95],"important":[96],"variables.":[97],"An":[98],"analysis":[99],"of":[100,109],"China\u2019s":[101],"provincial":[102],"economic":[103],"further":[105],"supports":[106],"merits":[108],"method.":[112]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-02-13T13:36:01.753593","created_date":"2025-10-10T00:00:00"}