{"id":"https://openalex.org/W2921855278","doi":"https://doi.org/10.1080/03610918.2019.1583343","title":"Marginal regression of recurrent gap times based on semiparametric transformation cure model","display_name":"Marginal regression of recurrent gap times based on semiparametric transformation cure model","publication_year":2019,"publication_date":"2019-03-12","ids":{"openalex":"https://openalex.org/W2921855278","doi":"https://doi.org/10.1080/03610918.2019.1583343","mag":"2921855278"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2019.1583343","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1583343","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/A5058562614","display_name":"Pao\u2010Sheng Shen","orcid":"https://orcid.org/0000-0001-6050-8648"},"institutions":[{"id":"https://openalex.org/I169090423","display_name":"Tunghai University","ror":"https://ror.org/00zhvdn11","country_code":"TW","type":"education","lineage":["https://openalex.org/I169090423"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Pao-Sheng Shen","raw_affiliation_strings":["Department of Statistics, Tunghai University, Taichung, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Tunghai University, Taichung, Taiwan","institution_ids":["https://openalex.org/I169090423"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100330480","display_name":"Yi Liu","orcid":"https://orcid.org/0000-0002-0261-3172"},"institutions":[{"id":"https://openalex.org/I169090423","display_name":"Tunghai University","ror":"https://ror.org/00zhvdn11","country_code":"TW","type":"education","lineage":["https://openalex.org/I169090423"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yi Liu","raw_affiliation_strings":["Department of Statistics, Tunghai University, Taichung, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Tunghai University, Taichung, Taiwan","institution_ids":["https://openalex.org/I169090423"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5058562614"],"corresponding_institution_ids":["https://openalex.org/I169090423"],"apc_list":null,"apc_paid":null,"fwci":0.9365,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.75600401,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"50","issue":"5","first_page":"1383","last_page":"1397"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9986000061035156,"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":0.9986000061035156,"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":0.9817000031471252,"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":0.9790999889373779,"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-regression","display_name":"Semiparametric regression","score":0.777692973613739},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7626718878746033},{"id":"https://openalex.org/keywords/censoring","display_name":"Censoring (clinical trials)","score":0.693702757358551},{"id":"https://openalex.org/keywords/semiparametric-model","display_name":"Semiparametric model","score":0.673786997795105},{"id":"https://openalex.org/keywords/estimating-equations","display_name":"Estimating equations","score":0.5892261862754822},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5045291185379028},{"id":"https://openalex.org/keywords/censored-regression-model","display_name":"Censored regression model","score":0.4598065912723541},{"id":"https://openalex.org/keywords/marginal-model","display_name":"Marginal model","score":0.4547225832939148},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4363485276699066},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4361634850502014},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.41003239154815674},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.37949132919311523},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.35360169410705566}],"concepts":[{"id":"https://openalex.org/C19539793","wikidata":"https://www.wikidata.org/wiki/Q7449609","display_name":"Semiparametric regression","level":3,"score":0.777692973613739},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7626718878746033},{"id":"https://openalex.org/C137668524","wikidata":"https://www.wikidata.org/wiki/Q189813","display_name":"Censoring (clinical trials)","level":2,"score":0.693702757358551},{"id":"https://openalex.org/C78297888","wikidata":"https://www.wikidata.org/wiki/Q7449607","display_name":"Semiparametric model","level":3,"score":0.673786997795105},{"id":"https://openalex.org/C204016326","wikidata":"https://www.wikidata.org/wiki/Q5401384","display_name":"Estimating equations","level":3,"score":0.5892261862754822},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5045291185379028},{"id":"https://openalex.org/C97379794","wikidata":"https://www.wikidata.org/wiki/Q4503892","display_name":"Censored regression model","level":3,"score":0.4598065912723541},{"id":"https://openalex.org/C197656967","wikidata":"https://www.wikidata.org/wiki/Q17058458","display_name":"Marginal model","level":3,"score":0.4547225832939148},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4363485276699066},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4361634850502014},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.41003239154815674},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.37949132919311523},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.35360169410705566}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2019.1583343","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1583343","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/16","display_name":"Peace, Justice and strong institutions","score":0.6100000143051147}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W107965176","https://openalex.org/W1494478641","https://openalex.org/W1504525887","https://openalex.org/W1969094789","https://openalex.org/W1973597307","https://openalex.org/W1984130041","https://openalex.org/W1989451794","https://openalex.org/W1991490253","https://openalex.org/W1994851329","https://openalex.org/W1997427494","https://openalex.org/W2007022861","https://openalex.org/W2011359741","https://openalex.org/W2013689038","https://openalex.org/W2014167632","https://openalex.org/W2016681503","https://openalex.org/W2016953948","https://openalex.org/W2024259756","https://openalex.org/W2037878235","https://openalex.org/W2042317864","https://openalex.org/W2051305724","https://openalex.org/W2054957279","https://openalex.org/W2055675509","https://openalex.org/W2061893665","https://openalex.org/W2061918355","https://openalex.org/W2068843761","https://openalex.org/W2077398160","https://openalex.org/W2092648747","https://openalex.org/W2134413432","https://openalex.org/W2137538399","https://openalex.org/W2166379450","https://openalex.org/W2168494806","https://openalex.org/W2401974674","https://openalex.org/W2916769551","https://openalex.org/W3022362511","https://openalex.org/W3147894994","https://openalex.org/W4246157667","https://openalex.org/W4253828197"],"related_works":["https://openalex.org/W2369772923","https://openalex.org/W1971606787","https://openalex.org/W4290879003","https://openalex.org/W3021457118","https://openalex.org/W2177212340","https://openalex.org/W3124245953","https://openalex.org/W2777153428","https://openalex.org/W2029512015","https://openalex.org/W2001200375","https://openalex.org/W4230969100"],"abstract_inverted_index":{"Recurrent":[0],"event":[1],"data":[2,92],"frequently":[3],"arise":[4],"in":[5,51],"longitudinal":[6],"studies.":[7],"In":[8],"this":[9,52],"article,":[10],"we":[11],"consider":[12],"a":[13],"marginal":[14],"semiparametric":[15],"transformation":[16],"cure":[17],"model":[18],"for":[19,44,93],"gap":[20],"times":[21],"between":[22],"recurrent":[23,91],"events.":[24],"We":[25,39],"assume":[26],"that":[27],"each":[28,37],"individual":[29],"has":[30],"the":[31,48,58,77,89],"possibility":[32],"of":[33,47,57,76,88],"being":[34],"cured":[35],"after":[36],"event.":[38],"proposed":[40,59,78,81],"generalized":[41],"estimating":[42],"equations":[43],"parameter":[45],"estimation":[46],"regression":[49],"parameters":[50],"model.":[53],"The":[54,80],"asymptotic":[55],"properties":[56,75],"estimators":[60],"are":[61],"established":[62],"under":[63],"independent":[64],"censoring.":[65],"A":[66],"simulation":[67],"study":[68],"is":[69,83],"conducted":[70],"to":[71],"investigate":[72],"finite":[73],"sample":[74],"estimators.":[79],"method":[82],"illustrated":[84],"using":[85],"an":[86],"example":[87],"tumor":[90],"bladder":[94],"cancer":[95],"patients.":[96]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}