{"id":"https://openalex.org/W2990026141","doi":"https://doi.org/10.1080/03610918.2019.1687720","title":"ICBayes: a package of Bayesian semiparametric regression for intervel-censored data","display_name":"ICBayes: a package of Bayesian semiparametric regression for intervel-censored data","publication_year":2019,"publication_date":"2019-11-23","ids":{"openalex":"https://openalex.org/W2990026141","doi":"https://doi.org/10.1080/03610918.2019.1687720","mag":"2990026141"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2019.1687720","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1687720","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/A5102779100","display_name":"Chun Pan","orcid":"https://orcid.org/0000-0003-0011-5599"},"institutions":[{"id":"https://openalex.org/I39694355","display_name":"Hunter College","ror":"https://ror.org/00g2xk477","country_code":"US","type":"education","lineage":["https://openalex.org/I39694355"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chun Pan","raw_affiliation_strings":["Department of Mathematics and Statistics, Hunter College, New York, New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Hunter College, New York, New York, USA","institution_ids":["https://openalex.org/I39694355"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101909735","display_name":"Bo Cai","orcid":"https://orcid.org/0000-0001-9386-8762"},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bo Cai","raw_affiliation_strings":["Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, South Carolina, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, South Carolina, USA","institution_ids":["https://openalex.org/I155781252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101677295","display_name":"Lianming Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lianming Wang","raw_affiliation_strings":["Department of Statistics, University of South Carolina, Columbia, South Carolina, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of South Carolina, Columbia, South Carolina, USA","institution_ids":["https://openalex.org/I155781252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064719403","display_name":"Xiaoyan Lin","orcid":"https://orcid.org/0000-0003-2348-7977"},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaoyan Lin","raw_affiliation_strings":["Department of Statistics, University of South Carolina, Columbia, South Carolina, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of South Carolina, Columbia, South Carolina, USA","institution_ids":["https://openalex.org/I155781252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5102779100"],"corresponding_institution_ids":["https://openalex.org/I39694355"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16901239,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"51","issue":"4","first_page":"1852","last_page":"1866"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9983000159263611,"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":0.9983000159263611,"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":0.9918000102043152,"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":0.9876999855041504,"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/proportional-hazards-model","display_name":"Proportional hazards model","score":0.6035435199737549},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5669663548469543},{"id":"https://openalex.org/keywords/r-package","display_name":"R package","score":0.5481118559837341},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5357038378715515},{"id":"https://openalex.org/keywords/accelerated-failure-time-model","display_name":"Accelerated failure time model","score":0.5334373116493225},{"id":"https://openalex.org/keywords/semiparametric-regression","display_name":"Semiparametric regression","score":0.49095895886421204},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4618505537509918},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.44459396600723267},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.4217967391014099},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.41948190331459045},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3627665936946869},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.34191030263900757},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30913835763931274}],"concepts":[{"id":"https://openalex.org/C50382708","wikidata":"https://www.wikidata.org/wiki/Q223218","display_name":"Proportional hazards model","level":2,"score":0.6035435199737549},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5669663548469543},{"id":"https://openalex.org/C2984074130","wikidata":"https://www.wikidata.org/wiki/Q73539779","display_name":"R package","level":2,"score":0.5481118559837341},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5357038378715515},{"id":"https://openalex.org/C33114746","wikidata":"https://www.wikidata.org/wiki/Q4672282","display_name":"Accelerated failure time model","level":3,"score":0.5334373116493225},{"id":"https://openalex.org/C19539793","wikidata":"https://www.wikidata.org/wiki/Q7449609","display_name":"Semiparametric regression","level":3,"score":0.49095895886421204},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4618505537509918},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.44459396600723267},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.4217967391014099},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.41948190331459045},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3627665936946869},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.34191030263900757},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30913835763931274},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2019.1687720","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1687720","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":[{"display_name":"Reduced inequalities","score":0.6000000238418579,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W41222772","https://openalex.org/W1492534149","https://openalex.org/W1516406292","https://openalex.org/W1885409180","https://openalex.org/W1967396577","https://openalex.org/W1986529644","https://openalex.org/W1995780830","https://openalex.org/W2042439995","https://openalex.org/W2045490289","https://openalex.org/W2047274445","https://openalex.org/W2064207173","https://openalex.org/W2065234813","https://openalex.org/W2067845569","https://openalex.org/W2071009554","https://openalex.org/W2084696120","https://openalex.org/W2121493622","https://openalex.org/W2167834874","https://openalex.org/W2204383650","https://openalex.org/W2734934856","https://openalex.org/W4399647892","https://openalex.org/W6868847269","https://openalex.org/W6869539911","https://openalex.org/W6869622340","https://openalex.org/W6959755135"],"related_works":["https://openalex.org/W920448194","https://openalex.org/W2754214645","https://openalex.org/W3166225146","https://openalex.org/W2352849674","https://openalex.org/W2305250237","https://openalex.org/W2098082502","https://openalex.org/W2013045445","https://openalex.org/W2889804998","https://openalex.org/W4281652516","https://openalex.org/W3095837644"],"abstract_inverted_index":{"Interval-censored":[0],"data":[1,43,48,111],"arise":[2],"frequently":[3],"in":[4],"medical":[5],"studies":[6],"of":[7,15,36,77,98],"diseases":[8],"that":[9,84],"require":[10],"periodic":[11],"examinations":[12],"for":[13,38],"symptoms":[14],"interest,":[16],"such":[17],"as":[18],"disease-free":[19],"survival":[20,59],"(DFS).":[21],"This":[22],"paper":[23],"provides":[24],"an":[25],"introduction":[26],"to":[27,73],"the":[28,75,78,99],"R":[29,82],"package":[30,79,100],"ICBayes":[31,56],"which":[32],"implements":[33],"a":[34,105,113],"set":[35],"programs":[37],"analyzing":[39,104],"case":[40,45,106,114],"1":[41,115],"interval-censored":[42,47,108,116],"and":[44,66,91,112],"2":[46,107],"under":[49],"Bayesian":[50,86],"semiparametric":[51],"framework.":[52],"The":[53,96],"main":[54],"function":[55],"fits":[57],"commonly-used":[58],"regression":[60],"models:":[61],"proportional":[62,64,87,89],"hazards,":[63,88],"odds,":[65,90],"probit.":[67],"A":[68],"simulation":[69],"study":[70],"is":[71,101],"conducted":[72],"compare":[74],"performance":[76],"with":[80],"two":[81],"packages":[83],"fit":[85],"accelerated":[92],"failure":[93],"time":[94],"models.":[95],"use":[97],"illustrated":[102],"through":[103],"breast":[109],"cosmesis":[110],"animal":[117],"tumorigenicity":[118],"data.":[119]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}