{"id":"https://openalex.org/W3211888520","doi":"https://doi.org/10.1109/iccse51940.2021.9569301","title":"The convergence of semiparametric joint model for incomplete follow-up data","display_name":"The convergence of semiparametric joint model for incomplete follow-up data","publication_year":2021,"publication_date":"2021-08-17","ids":{"openalex":"https://openalex.org/W3211888520","doi":"https://doi.org/10.1109/iccse51940.2021.9569301","mag":"3211888520"},"language":"en","primary_location":{"id":"doi:10.1109/iccse51940.2021.9569301","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccse51940.2021.9569301","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 16th International Conference on Computer Science & Education (ICCSE)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100438820","display_name":"Yilin Li","orcid":"https://orcid.org/0000-0002-7378-8615"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yilin Li","raw_affiliation_strings":["College of Computer Science, Sichuan University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210125143"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113173262","display_name":"Yonghong Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yonghong Zhao","raw_affiliation_strings":["College of Mathematics, Sichuan University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22426177,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":null,"first_page":"800","last_page":"805"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9991999864578247,"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":0.9991999864578247,"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":0.9955000281333923,"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":0.989300012588501,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6707125306129456},{"id":"https://openalex.org/keywords/semiparametric-regression","display_name":"Semiparametric regression","score":0.6478387117385864},{"id":"https://openalex.org/keywords/asymptotic-distribution","display_name":"Asymptotic distribution","score":0.6224203109741211},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.620675265789032},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5994734764099121},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5738685131072998},{"id":"https://openalex.org/keywords/semiparametric-model","display_name":"Semiparametric model","score":0.5556671619415283},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5057132244110107},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.48040536046028137},{"id":"https://openalex.org/keywords/strong-consistency","display_name":"Strong consistency","score":0.4407292306423187},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4304325580596924},{"id":"https://openalex.org/keywords/joint-probability-distribution","display_name":"Joint probability distribution","score":0.4127906560897827},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.41195085644721985},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3803563117980957},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3718110918998718},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.14004585146903992}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6707125306129456},{"id":"https://openalex.org/C19539793","wikidata":"https://www.wikidata.org/wiki/Q7449609","display_name":"Semiparametric regression","level":3,"score":0.6478387117385864},{"id":"https://openalex.org/C65778772","wikidata":"https://www.wikidata.org/wiki/Q12345341","display_name":"Asymptotic distribution","level":3,"score":0.6224203109741211},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.620675265789032},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5994734764099121},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5738685131072998},{"id":"https://openalex.org/C78297888","wikidata":"https://www.wikidata.org/wiki/Q7449607","display_name":"Semiparametric model","level":3,"score":0.5556671619415283},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5057132244110107},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.48040536046028137},{"id":"https://openalex.org/C31388003","wikidata":"https://www.wikidata.org/wiki/Q7624548","display_name":"Strong consistency","level":3,"score":0.4407292306423187},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4304325580596924},{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.4127906560897827},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41195085644721985},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3803563117980957},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3718110918998718},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.14004585146903992}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccse51940.2021.9569301","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccse51940.2021.9569301","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 16th International Conference on Computer Science & Education (ICCSE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1974345349","https://openalex.org/W1976873809","https://openalex.org/W1997427494","https://openalex.org/W2013235090","https://openalex.org/W2059890351","https://openalex.org/W2070496276","https://openalex.org/W2079566573","https://openalex.org/W2082883684","https://openalex.org/W2120486543","https://openalex.org/W2134413432","https://openalex.org/W2139963961","https://openalex.org/W2141508928","https://openalex.org/W2304550728","https://openalex.org/W2802876434","https://openalex.org/W2955361554","https://openalex.org/W3147894994","https://openalex.org/W4285719527"],"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/W2384198123","https://openalex.org/W2356010924","https://openalex.org/W4385733650","https://openalex.org/W3167087793"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,35],"propose":[4],"a":[5,23,65],"joint":[6,75],"model":[7,24],"approach":[8],"using":[9],"shared":[10],"random":[11,19],"effects":[12],"to":[13],"measure":[14],"the":[15,37,44,57,74],"correlation":[16],"of":[17],"two":[18],"variable.":[20],"We":[21,49],"use":[22],"transformation":[25],"method":[26],"which":[27],"can":[28],"apply":[29],"on":[30],"more":[31],"general":[32],"distributions.":[33],"Moreover,":[34],"establish":[36],"consistency":[38],"and":[39,59],"asymptotic":[40],"normality":[41],"results":[42,63],"for":[43,55,68],"semiparametric":[45],"maximum":[46],"likelihood":[47],"estimator.":[48],"also":[50],"derive":[51],"consistent":[52],"variance":[53],"estimates":[54],"both":[56],"parametric":[58],"nonparametric":[60],"components.":[61],"The":[62],"provide":[64],"theoretical":[66],"foundation":[67],"making":[69],"large":[70],"sample":[71],"inference":[72],"under":[73],"model.":[76]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}