{"id":"https://openalex.org/W2552154562","doi":"https://doi.org/10.1080/03610918.2016.1255968","title":"Piecewise Cox models with right-censored data","display_name":"Piecewise Cox models with right-censored data","publication_year":2016,"publication_date":"2016-11-18","ids":{"openalex":"https://openalex.org/W2552154562","doi":"https://doi.org/10.1080/03610918.2016.1255968","mag":"2552154562"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2016.1255968","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2016.1255968","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/A5112783991","display_name":"George Y. Wong","orcid":null},"institutions":[{"id":"https://openalex.org/I1287643137","display_name":"Mount Sinai Beth Israel","ror":"https://ror.org/01742jq13","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1287643137","https://openalex.org/I1320796813"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"George Y. C. Wong","raw_affiliation_strings":["Department of Integrative Medicine, Mount Sinai Beth Israel, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Integrative Medicine, Mount Sinai Beth Israel, New York, NY, USA","institution_ids":["https://openalex.org/I1287643137"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102828179","display_name":"Michael P. Osborne","orcid":"https://orcid.org/0000-0002-3738-5587"},"institutions":[{"id":"https://openalex.org/I4210101825","display_name":"Strang Cancer Prevention Institute","ror":"https://ror.org/01d7ffm04","country_code":"US","type":"education","lineage":["https://openalex.org/I4210101825"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael P. Osborne","raw_affiliation_strings":["Strang Cancer Prevention Institute, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Strang Cancer Prevention Institute, New York, NY, USA","institution_ids":["https://openalex.org/I4210101825"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068779193","display_name":"Qinggang Diao","orcid":null},"institutions":[{"id":"https://openalex.org/I123946342","display_name":"Binghamton University","ror":"https://ror.org/008rmbt77","country_code":"US","type":"education","lineage":["https://openalex.org/I123946342"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qinggang Diao","raw_affiliation_strings":["Department of Mathematical Sciences, SUNY, Binghamton, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences, SUNY, Binghamton, NY, USA","institution_ids":["https://openalex.org/I123946342"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001159585","display_name":"Qiqing Yu","orcid":"https://orcid.org/0000-0002-2376-4789"},"institutions":[{"id":"https://openalex.org/I123946342","display_name":"Binghamton University","ror":"https://ror.org/008rmbt77","country_code":"US","type":"education","lineage":["https://openalex.org/I123946342"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Qiqing Yu","raw_affiliation_strings":["Department of Mathematical Sciences, SUNY, Binghamton, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences, SUNY, Binghamton, NY, USA","institution_ids":["https://openalex.org/I123946342"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5001159585"],"corresponding_institution_ids":["https://openalex.org/I123946342"],"apc_list":null,"apc_paid":null,"fwci":2.2162,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.89253745,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"46","issue":"10","first_page":"7894","last_page":"7908"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9970999956130981,"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/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9970999956130981,"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":0.994700014591217,"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":0.9936000108718872,"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":0.7558597326278687},{"id":"https://openalex.org/keywords/piecewise","display_name":"Piecewise","score":0.7436028122901917},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.612212061882019},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.5733679533004761},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5544900298118591},{"id":"https://openalex.org/keywords/efficiency","display_name":"Efficiency","score":0.5333765745162964},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5212576985359192},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5113224983215332},{"id":"https://openalex.org/keywords/proportional-hazards-model","display_name":"Proportional hazards model","score":0.5009670257568359},{"id":"https://openalex.org/keywords/parametric-model","display_name":"Parametric model","score":0.49250730872154236},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.47118356823921204},{"id":"https://openalex.org/keywords/likelihood-function","display_name":"Likelihood function","score":0.4285883605480194},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4278773367404938},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.41379058361053467},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2939077615737915},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.19381985068321228},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.06731650233268738}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7558597326278687},{"id":"https://openalex.org/C164660894","wikidata":"https://www.wikidata.org/wiki/Q2037833","display_name":"Piecewise","level":2,"score":0.7436028122901917},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.612212061882019},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.5733679533004761},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5544900298118591},{"id":"https://openalex.org/C17648541","wikidata":"https://www.wikidata.org/wiki/Q2265984","display_name":"Efficiency","level":3,"score":0.5333765745162964},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5212576985359192},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5113224983215332},{"id":"https://openalex.org/C50382708","wikidata":"https://www.wikidata.org/wiki/Q223218","display_name":"Proportional hazards model","level":2,"score":0.5009670257568359},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.49250730872154236},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.47118356823921204},{"id":"https://openalex.org/C89106044","wikidata":"https://www.wikidata.org/wiki/Q45284","display_name":"Likelihood function","level":3,"score":0.4285883605480194},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4278773367404938},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.41379058361053467},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2939077615737915},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.19381985068321228},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.06731650233268738},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2016.1255968","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2016.1255968","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","score":0.6200000047683716,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1570622790","https://openalex.org/W1997403101","https://openalex.org/W2013245256","https://openalex.org/W2048941211","https://openalex.org/W2066927337","https://openalex.org/W2068503417","https://openalex.org/W2080373387","https://openalex.org/W2087407897","https://openalex.org/W2091982107","https://openalex.org/W2123497409","https://openalex.org/W2136883754","https://openalex.org/W2168912024","https://openalex.org/W2796700885"],"related_works":["https://openalex.org/W2013921918","https://openalex.org/W2019724159","https://openalex.org/W4280508323","https://openalex.org/W2149766606","https://openalex.org/W2371672232","https://openalex.org/W3151346708","https://openalex.org/W2088686292","https://openalex.org/W2540019423","https://openalex.org/W2103185490","https://openalex.org/W1040520765"],"abstract_inverted_index":{"We":[0,9],"study":[1,39],"a":[2,27],"general":[3],"class":[4],"of":[5,13,20,45,48,63,67],"piecewise":[6],"Cox":[7],"models.":[8],"discuss":[10],"the":[11,14,21,31,42,46,49,52,60,64,68,73,81,87],"computation":[12],"semi-parametric":[15],"maximum":[16,32],"likelihood":[17,34],"estimates":[18,35],"(SMLE)":[19],"parameters,":[22],"with":[23],"right-censored":[24],"data,":[25],"and":[26],"simplified":[28],"algorithm":[29],"for":[30],"partial":[33],"(MPLE).":[36],"Our":[37],"simulation":[38],"suggests":[40],"that":[41],"relative":[43,61],"efficiency":[44,62],"PMLE":[47],"parameter":[50],"to":[51,57,72,78],"SMLE":[53,74,82],"ranges":[54,75],"from":[55,76],"96%":[56],"99.9%,":[58],"but":[59],"existing":[65,88],"estimators":[66],"baseline":[69],"survival":[70],"function":[71],"3%":[77],"24%.":[79],"Thus,":[80],"is":[83],"much":[84],"better":[85],"than":[86],"estimators.":[89]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3}],"updated_date":"2026-03-24T08:02:53.985720","created_date":"2025-10-10T00:00:00"}