{"id":"https://openalex.org/W3210309470","doi":"https://doi.org/10.1080/03610918.2021.1995753","title":"Generalized Birnbaum\u2013Saunders mixture cure frailty model: inferential method and an application to bone marrow transplant data","display_name":"Generalized Birnbaum\u2013Saunders mixture cure frailty model: inferential method and an application to bone marrow transplant data","publication_year":2021,"publication_date":"2021-11-02","ids":{"openalex":"https://openalex.org/W3210309470","doi":"https://doi.org/10.1080/03610918.2021.1995753","mag":"3210309470"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2021.1995753","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2021.1995753","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/A5100399887","display_name":"Kai Liu","orcid":"https://orcid.org/0000-0002-3936-7585"},"institutions":[{"id":"https://openalex.org/I146613903","display_name":"Shanghai Lixin University of Accounting and Finance","ror":"https://ror.org/02g81yf77","country_code":"CN","type":"education","lineage":["https://openalex.org/I146613903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Liu","raw_affiliation_strings":["School of Statistics and Mathematics, Interdisciplinary Research Institute of Data Science, Shanghai Lixin University of Accounting and Finance, Shanghai, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Statistics and Mathematics, Interdisciplinary Research Institute of Data Science, Shanghai Lixin University of Accounting and Finance, Shanghai, P.R. China","institution_ids":["https://openalex.org/I146613903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039956503","display_name":"N. Balakrishnan","orcid":"https://orcid.org/0000-0001-5842-8892"},"institutions":[{"id":"https://openalex.org/I98251732","display_name":"McMaster University","ror":"https://ror.org/02fa3aq29","country_code":"CA","type":"education","lineage":["https://openalex.org/I98251732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Narayanaswamy Balakrishnan","raw_affiliation_strings":["Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario, Canada","institution_ids":["https://openalex.org/I98251732"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012364939","display_name":"Mu He","orcid":"https://orcid.org/0000-0002-0085-7181"},"institutions":[{"id":"https://openalex.org/I69356397","display_name":"Xi\u2019an Jiaotong-Liverpool University","ror":"https://ror.org/03zmrmn05","country_code":"CN","type":"education","lineage":["https://openalex.org/I69356397"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mu He","raw_affiliation_strings":["The Department of Foundational Mathematics, Xi\u2019an Jiaotong-Liverpool University, Suzhou, P.R. China","The Department of Foundational Mathematics, Xi'an Jiaotong-Liverpool University, Suzhou, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Department of Foundational Mathematics, Xi\u2019an Jiaotong-Liverpool University, Suzhou, P.R. China","institution_ids":["https://openalex.org/I69356397"]},{"raw_affiliation_string":"The Department of Foundational Mathematics, Xi'an Jiaotong-Liverpool University, Suzhou, P.R. China","institution_ids":["https://openalex.org/I69356397"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5012364939"],"corresponding_institution_ids":["https://openalex.org/I69356397"],"apc_list":null,"apc_paid":null,"fwci":0.273,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.63794779,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"52","issue":"11","first_page":"5655","last_page":"5679"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9966999888420105,"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"}},"topics":[{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9966999888420105,"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/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9959999918937683,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9952999949455261,"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/inference","display_name":"Inference","score":0.7151997089385986},{"id":"https://openalex.org/keywords/unobservable","display_name":"Unobservable","score":0.584531307220459},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5838510990142822},{"id":"https://openalex.org/keywords/likelihood-function","display_name":"Likelihood function","score":0.4895130395889282},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.4875637888908386},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.44130876660346985},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44074922800064087},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.436532199382782},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.4112131595611572},{"id":"https://openalex.org/keywords/marginal-likelihood","display_name":"Marginal likelihood","score":0.41106700897216797},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3999265432357788},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37618863582611084},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30553480982780457},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3051221966743469},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1136009693145752}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7151997089385986},{"id":"https://openalex.org/C2780695315","wikidata":"https://www.wikidata.org/wiki/Q3799040","display_name":"Unobservable","level":2,"score":0.584531307220459},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5838510990142822},{"id":"https://openalex.org/C89106044","wikidata":"https://www.wikidata.org/wiki/Q45284","display_name":"Likelihood function","level":3,"score":0.4895130395889282},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.4875637888908386},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.44130876660346985},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44074922800064087},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.436532199382782},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.4112131595611572},{"id":"https://openalex.org/C95923904","wikidata":"https://www.wikidata.org/wiki/Q6760420","display_name":"Marginal likelihood","level":3,"score":0.41106700897216797},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3999265432357788},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37618863582611084},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30553480982780457},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3051221966743469},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1136009693145752}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2021.1995753","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2021.1995753","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":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5199999809265137},{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.4699999988079071}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1964825543","https://openalex.org/W1978358551","https://openalex.org/W1992910292","https://openalex.org/W2013885224","https://openalex.org/W2029359551","https://openalex.org/W2033796225","https://openalex.org/W2034414512","https://openalex.org/W2047708357","https://openalex.org/W2056124784","https://openalex.org/W2059989630","https://openalex.org/W2062216160","https://openalex.org/W2062637647","https://openalex.org/W2076610368","https://openalex.org/W2078223516","https://openalex.org/W2078247886","https://openalex.org/W2092660489","https://openalex.org/W2110863526","https://openalex.org/W2126957488","https://openalex.org/W2143887617","https://openalex.org/W2152559857","https://openalex.org/W2153045803","https://openalex.org/W2330491673","https://openalex.org/W2616597342","https://openalex.org/W2886390568","https://openalex.org/W2887410224","https://openalex.org/W2895222134","https://openalex.org/W2963358298","https://openalex.org/W2976657055","https://openalex.org/W2978746793","https://openalex.org/W2987549251","https://openalex.org/W4399034923"],"related_works":["https://openalex.org/W4388397594","https://openalex.org/W2356093187","https://openalex.org/W164417758","https://openalex.org/W2013921918","https://openalex.org/W2186819079","https://openalex.org/W4287728430","https://openalex.org/W4233488282","https://openalex.org/W2794631075","https://openalex.org/W3040609822","https://openalex.org/W2019724159"],"abstract_inverted_index":{"Cluster":[0],"time":[1],"data":[2],"are":[3,45,106,115],"commonly":[4],"encountered":[5],"in":[6,91],"survival":[7],"analysis":[8,152],"due":[9,47],"to":[10,27,30,48,169],"unobservable":[11],"factors":[12],"such":[13,22],"as":[14],"shared":[15],"environmental":[16],"conditions":[17],"and":[18,55,74,112,140,158,177],"genetic":[19],"similarity.":[20],"In":[21],"cases,":[23],"careful":[24],"attention":[25],"needs":[26],"be":[28],"paid":[29],"model":[31,84,113,136,176],"the":[32,36,39,81,88,92,96,102,121,124,134,141,154,171,174,178],"possible":[33],"correlation":[34],"between":[35],"subjects":[37],"within":[38],"same":[40],"cluster.":[41],"Moreover,":[42],"some":[43],"diseases":[44],"curable":[46],"great":[49],"advances":[50],"on":[51,164],"modern":[52],"medical":[53],"techniques":[54],"treatments.":[56],"For":[57],"tracking":[58],"these":[59],"issues,":[60],"we":[61,149],"consider":[62],"here":[63],"a":[64,76],"mixture":[65],"cure":[66],"frailty":[67,72],"model,":[68],"with":[69],"generalized":[70],"Birnbaum\u2013Saunders":[71],"distribution,":[73],"propose":[75],"marginal":[77],"likelihood":[78,93,104],"approach":[79],"for":[80,119],"estimation":[82],"of":[83,98,123,143,153,156,173,180],"parameter.":[85],"We":[86],"approximate":[87],"intractable":[89],"integrals":[90],"function":[94],"by":[95],"use":[97],"Monte-Carlo":[99],"method.":[100],"Thereafter,":[101],"maximum":[103],"estimates":[105],"numerically":[107],"determined.":[108],"A":[109],"simulation":[110],"study":[111,132],"discrimination":[114],"then":[116],"carried":[117],"out":[118],"evaluating":[120],"performance":[122],"proposed":[125,135,175],"model.":[126],"It":[127],"is":[128,145],"observed":[129],"from":[130],"this":[131],"that":[133],"provides":[137],"more":[138],"flexibility":[139],"method":[142,179],"inference":[144],"quite":[146],"robust.":[147],"Finally,":[148],"conduct":[150],"an":[151],"effects":[155],"allogeneic":[157],"autologous":[159],"bone":[160],"marrow":[161],"transplant":[162],"treatments":[163],"acute":[165],"lymphoblastic":[166],"leukemia":[167],"patients":[168],"demonstrate":[170],"usefulness":[172],"inference.":[181]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}