{"id":"https://openalex.org/W2564410009","doi":"https://doi.org/10.1080/03610918.2015.1005230","title":"Weighting methods for ties between event times and covariate change times","display_name":"Weighting methods for ties between event times and covariate change times","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2564410009","doi":"https://doi.org/10.1080/03610918.2015.1005230","mag":"2564410009"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2015.1005230","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2015.1005230","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/A5100393243","display_name":"Xin Xin","orcid":"https://orcid.org/0000-0002-0965-5930"},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Xin Xin","raw_affiliation_strings":["Department of Mathematics and Statistics, University of Guelph, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, University of Guelph, Ontario, Canada","institution_ids":["https://openalex.org/I79817857"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086963365","display_name":"Julie Horrocks","orcid":"https://orcid.org/0000-0001-5857-7636"},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Julie Horrocks","raw_affiliation_strings":["Department of Mathematics and Statistics, University of Guelph, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, University of Guelph, Ontario, Canada","institution_ids":["https://openalex.org/I79817857"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074823254","display_name":"Gerarda Darlington","orcid":"https://orcid.org/0000-0001-8812-0362"},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Gerarda A. Darlington","raw_affiliation_strings":["Department of Mathematics and Statistics, University of Guelph, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, University of Guelph, Ontario, Canada","institution_ids":["https://openalex.org/I79817857"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5086963365"],"corresponding_institution_ids":["https://openalex.org/I79817857"],"apc_list":null,"apc_paid":null,"fwci":2.7273,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.92418095,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"47","issue":"1","first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.992900013923645,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.992900013923645,"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/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9883999824523926,"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":0.9858999848365784,"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/covariate","display_name":"Covariate","score":0.7675768733024597},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.6734018325805664},{"id":"https://openalex.org/keywords/jump","display_name":"Jump","score":0.631934404373169},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.6213984489440918},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.6213764548301697},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5751832723617554},{"id":"https://openalex.org/keywords/standard-error","display_name":"Standard error","score":0.5513179898262024},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4827258288860321},{"id":"https://openalex.org/keywords/proportional-hazards-model","display_name":"Proportional hazards model","score":0.4300300180912018},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.32152512669563293}],"concepts":[{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.7675768733024597},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.6734018325805664},{"id":"https://openalex.org/C2780695682","wikidata":"https://www.wikidata.org/wiki/Q4005959","display_name":"Jump","level":2,"score":0.631934404373169},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.6213984489440918},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.6213764548301697},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5751832723617554},{"id":"https://openalex.org/C18747219","wikidata":"https://www.wikidata.org/wiki/Q620994","display_name":"Standard error","level":2,"score":0.5513179898262024},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4827258288860321},{"id":"https://openalex.org/C50382708","wikidata":"https://www.wikidata.org/wiki/Q223218","display_name":"Proportional hazards model","level":2,"score":0.4300300180912018},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.32152512669563293},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2015.1005230","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2015.1005230","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":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1570622790","https://openalex.org/W1979816698","https://openalex.org/W1992464801","https://openalex.org/W1995945562","https://openalex.org/W2015635614","https://openalex.org/W2036464901","https://openalex.org/W2048030130","https://openalex.org/W2103338349","https://openalex.org/W2109533003","https://openalex.org/W2138986862","https://openalex.org/W2160842550","https://openalex.org/W2171720857","https://openalex.org/W2582743722","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2180954594","https://openalex.org/W2052835778","https://openalex.org/W2985746494","https://openalex.org/W4206042385","https://openalex.org/W2049003611","https://openalex.org/W2511384863","https://openalex.org/W2080773131","https://openalex.org/W2109980432","https://openalex.org/W44636601","https://openalex.org/W2938354773"],"abstract_inverted_index":{"Recent":[0],"work":[1],"has":[2],"shown":[3],"that":[4,16,80],"the":[5,14,32,41,49,57,60,64,70,81,88,95,102,106,112,129,132,145,149,157],"presence":[6],"of":[7,28,48,59,63,105,131],"ties":[8],"between":[9],"an":[10],"outcome":[11],"event":[12,89],"and":[13,69,118,148,173],"time":[15],"a":[17,170],"binary":[18],"covariate":[19],"changes":[20],"or":[21,86],"jumps":[22],"can":[23],"lead":[24],"to":[25,55,100,162],"biased":[26],"estimates":[27,62],"regression":[29,146],"coefficients":[30],"in":[31,120],"Cox":[33],"proportional":[34],"hazards":[35],"model.":[36],"One":[37],"proposed":[38,158],"solution":[39],"is":[40,53],"Equally":[42,50,107,133],"Weighted":[43,51,108,134],"method.":[44],"The":[45,164],"coefficient":[46,61,109,147],"estimate":[47,101],"method":[52,68,97],"defined":[54],"be":[56],"average":[58],"Jump":[65,71],"Before":[66],"Event":[67,73],"After":[72],"method,":[74],"where":[75],"these":[76],"two":[77,125,177],"methods":[78,127,141,159,166],"assume":[79],"jump":[82],"always":[83],"occurs":[84],"before":[85],"after":[87],"time,":[90],"respectively.":[91],"In":[92,122],"previous":[93],"work,":[94],"bootstrap":[96,113],"was":[98,115],"used":[99],"standard":[103,135,151],"error":[104,136,152],"estimate.":[110],"However,":[111],"approach":[114],"computationally":[116],"intensive":[117],"resulted":[119],"overestimation.":[121],"this":[123],"article,":[124],"new":[126],"for":[128,142],"estimation":[130],"are":[137,153,160,167,174],"proposed.":[138,155],"Three":[139],"alternative":[140],"estimating":[143],"both":[144],"corresponding":[150],"also":[154],"All":[156],"easy":[161],"implement.":[163],"five":[165],"investigated":[168],"using":[169,176],"simulation":[171],"study":[172],"illustrated":[175],"real":[178],"datasets.":[179]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
