{"id":"https://openalex.org/W2914483702","doi":"https://doi.org/10.1080/03610918.2018.1547396","title":"A new orthogonality empirical likelihood for varying coefficient partially linear instrumental variable models with longitudinal data","display_name":"A new orthogonality empirical likelihood for varying coefficient partially linear instrumental variable models with longitudinal data","publication_year":2019,"publication_date":"2019-01-22","ids":{"openalex":"https://openalex.org/W2914483702","doi":"https://doi.org/10.1080/03610918.2018.1547396","mag":"2914483702"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2018.1547396","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2018.1547396","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/A5057781643","display_name":"Peixin Zhao","orcid":"https://orcid.org/0000-0001-5701-3708"},"institutions":[{"id":"https://openalex.org/I145581781","display_name":"Chongqing Technology and Business University","ror":"https://ror.org/05hqf1284","country_code":"CN","type":"education","lineage":["https://openalex.org/I145581781"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peixin Zhao","raw_affiliation_strings":["Chongqing Key Laboratory of Social Economy and Applied Statistics, Chongqing, China;","College of Mathematics and Statistics, Chongqing Technology and Business University, Chongqing, China;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing Key Laboratory of Social Economy and Applied Statistics, Chongqing, China;","institution_ids":[]},{"raw_affiliation_string":"College of Mathematics and Statistics, Chongqing Technology and Business University, Chongqing, China;","institution_ids":["https://openalex.org/I145581781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083168362","display_name":"Xiaoshuang Zhou","orcid":"https://orcid.org/0000-0001-6610-6834"},"institutions":[{"id":"https://openalex.org/I4210165547","display_name":"Dezhou University","ror":"https://ror.org/05mnjs436","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210165547"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoshuang Zhou","raw_affiliation_strings":["School of Mathematical Sciences, Dezhou University, Shandong Dezhou, China;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, Dezhou University, Shandong Dezhou, China;","institution_ids":["https://openalex.org/I4210165547"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100439026","display_name":"Xiuli Wang","orcid":"https://orcid.org/0000-0001-8550-0941"},"institutions":[{"id":"https://openalex.org/I28006308","display_name":"Shandong Normal University","ror":"https://ror.org/01wy3h363","country_code":"CN","type":"education","lineage":["https://openalex.org/I28006308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuli Wang","raw_affiliation_strings":["School of Mathematical Sciences, Shandong Normal University, Shandong Jinan, China;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, Shandong Normal University, Shandong Jinan, China;","institution_ids":["https://openalex.org/I28006308"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084820506","display_name":"Xingshou Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210161599","display_name":"Hechi University","ror":"https://ror.org/05pjkyk24","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210161599"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingshou Huang","raw_affiliation_strings":["College of Mathematics and Statistics, Hechi University, Guangxi Yizhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Statistics, Hechi University, Guangxi Yizhou, China","institution_ids":["https://openalex.org/I4210161599"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5083168362"],"corresponding_institution_ids":["https://openalex.org/I4210165547"],"apc_list":null,"apc_paid":null,"fwci":0.6786,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.69770239,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"49","issue":"12","first_page":"3328","last_page":"3344"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9976999759674072,"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":0.9976999759674072,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9943000078201294,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9873999953269958,"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/estimator","display_name":"Estimator","score":0.7620331048965454},{"id":"https://openalex.org/keywords/orthogonality","display_name":"Orthogonality","score":0.7512279152870178},{"id":"https://openalex.org/keywords/empirical-likelihood","display_name":"Empirical likelihood","score":0.7310750484466553},{"id":"https://openalex.org/keywords/instrumental-variable","display_name":"Instrumental variable","score":0.6469136476516724},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6326791644096375},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.601889967918396},{"id":"https://openalex.org/keywords/generalized-method-of-moments","display_name":"Generalized method of moments","score":0.5557982921600342},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5066962838172913},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.4778313636779785},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.47781994938850403},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.434345543384552},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.4336518943309784},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4111097455024719},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.32756495475769043},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.23540708422660828},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1063569188117981}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7620331048965454},{"id":"https://openalex.org/C17137986","wikidata":"https://www.wikidata.org/wiki/Q215067","display_name":"Orthogonality","level":2,"score":0.7512279152870178},{"id":"https://openalex.org/C2781117939","wikidata":"https://www.wikidata.org/wiki/Q5374245","display_name":"Empirical likelihood","level":3,"score":0.7310750484466553},{"id":"https://openalex.org/C162144332","wikidata":"https://www.wikidata.org/wiki/Q1665305","display_name":"Instrumental variable","level":2,"score":0.6469136476516724},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6326791644096375},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.601889967918396},{"id":"https://openalex.org/C162748667","wikidata":"https://www.wikidata.org/wiki/Q683131","display_name":"Generalized method of moments","level":3,"score":0.5557982921600342},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5066962838172913},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.4778313636779785},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.47781994938850403},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.434345543384552},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.4336518943309784},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4111097455024719},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.32756495475769043},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.23540708422660828},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1063569188117981},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2018.1547396","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2018.1547396","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1935597517","https://openalex.org/W1965236914","https://openalex.org/W1974234363","https://openalex.org/W1989439593","https://openalex.org/W1995286197","https://openalex.org/W2002306002","https://openalex.org/W2027323119","https://openalex.org/W2037645235","https://openalex.org/W2042041101","https://openalex.org/W2055275378","https://openalex.org/W2066906300","https://openalex.org/W2082950433","https://openalex.org/W2084626053","https://openalex.org/W2090280380","https://openalex.org/W2090309891","https://openalex.org/W2104149246","https://openalex.org/W2129977812","https://openalex.org/W2149860264","https://openalex.org/W2169013499","https://openalex.org/W2172523399","https://openalex.org/W2258317305","https://openalex.org/W2592787351","https://openalex.org/W2752368500","https://openalex.org/W2766375325","https://openalex.org/W2784404164","https://openalex.org/W3100684276"],"related_works":["https://openalex.org/W2142995921","https://openalex.org/W3123063552","https://openalex.org/W3124296889","https://openalex.org/W2083485815","https://openalex.org/W3125150276","https://openalex.org/W1547506455","https://openalex.org/W1593911989","https://openalex.org/W1820099800","https://openalex.org/W3150788171","https://openalex.org/W2083188108"],"abstract_inverted_index":{"Varying":[0],"coefficient":[1,54],"partially":[2,55],"linear":[3,56],"models":[4,59],"are":[5],"usually":[6],"used":[7],"for":[8],"longitudinal":[9,61],"data":[10,114],"analysis,":[11],"and":[12,28,46,71,74,111],"an":[13],"interest":[14],"is":[15,105],"mainly":[16],"to":[17,43],"improve":[18],"efficiency":[19],"of":[20,52,92,101],"regression":[21],"coefficients.":[22],"By":[23],"the":[24,29,69,75,93,97,102],"orthogonality":[25],"estimation":[26],"technology":[27],"empirical":[30,39],"likelihood":[31,40],"inference":[32,41],"method,":[33],"we":[34,87],"propose":[35],"a":[36,50,112],"new":[37],"orthogonality-based":[38],"method":[42],"estimate":[44,68],"parameter":[45],"nonparametric":[47,72],"components":[48],"in":[49],"class":[51],"varying":[53],"instrumental":[57],"variable":[58],"with":[60],"data.":[62],"The":[63],"proposed":[64,103],"procedure":[65,104],"can":[66],"separately":[67],"parametric":[70],"components,":[73],"resulting":[76,94],"estimators":[77],"do":[78],"not":[79],"affect":[80],"each":[81],"other.":[82],"Under":[83],"some":[84,89,108],"mild":[85],"conditions,":[86],"establish":[88],"asymptotic":[90],"properties":[91],"estimators.":[95],"Furthermore,":[96],"finite":[98],"sample":[99],"performance":[100],"assessed":[106],"by":[107],"simulation":[109],"experiments":[110],"real":[113],"analysis.":[115]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
