{"id":"https://openalex.org/W4309288288","doi":"https://doi.org/10.1111/rssa.12937","title":"Wei Zhong, Chuang Wan and Changliang Zou's contribution to the \u2018First Discussion Meeting on Statistical Aspects of the Covid-19 Pandemic\u2019","display_name":"Wei Zhong, Chuang Wan and Changliang Zou's contribution to the \u2018First Discussion Meeting on Statistical Aspects of the Covid-19 Pandemic\u2019","publication_year":2022,"publication_date":"2022-10-01","ids":{"openalex":"https://openalex.org/W4309288288","doi":"https://doi.org/10.1111/rssa.12937"},"language":"en","primary_location":{"id":"doi:10.1111/rssa.12937","doi":"https://doi.org/10.1111/rssa.12937","is_oa":false,"landing_page_url":"https://doi.org/10.1111/rssa.12937","pdf_url":null,"source":{"id":"https://openalex.org/S185328345","display_name":"Journal of the Royal Statistical Society Series A (Statistics in Society)","issn_l":"0964-1998","issn":["0964-1998","1467-985X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","cwts-core","doyens","jufo-2","ki-jl-2","norway-2"],"host_organization":"https://openalex.org/P4310311763","host_organization_name":"Royal Statistical Society","host_organization_lineage":["https://openalex.org/P4310311763"],"host_organization_lineage_names":["Royal Statistical Society"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Royal Statistical Society Series A: Statistics in Society","raw_type":"journal-article"},"volume":null,"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/A5101909485","display_name":"Wei Zhong","orcid":"https://orcid.org/0000-0002-0551-7848","observed_orcids":["https://orcid.org/0000-0002-0551-7848","https://orcid.org/0009-0002-0518-0066"]},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Zhong","raw_affiliation_strings":["Xiamen University , Xiamen, Fujian , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiamen University , Xiamen, Fujian , China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006454556","display_name":"Chuang Wan","orcid":"https://orcid.org/0009-0002-8714-7488","observed_orcids":["https://orcid.org/0009-0002-8714-7488"]},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuang Wan","raw_affiliation_strings":["Xiamen University , Xiamen, Fujian , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiamen University , Xiamen, Fujian , China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007454142","display_name":"Changliang Zou","orcid":"https://orcid.org/0000-0003-2943-7612","observed_orcids":["https://orcid.org/0000-0003-2943-7612"]},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changliang Zou","raw_affiliation_strings":["Nankai University , Tianjin , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nankai University , Tianjin , China","institution_ids":["https://openalex.org/I205237279"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101909485"],"corresponding_institution_ids":["https://openalex.org/I191208505"],"apc_list":{"value":2400,"currency":"GBP","value_usd":3600},"apc_paid":null,"fwci":0.2909,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.54314266,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":95},"biblio":{"volume":"185","issue":"4","first_page":"1841","last_page":"1843"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10410","display_name":"COVID-19 epidemiological studies","score":0.6333000063896179,"subfield":{"id":"https://openalex.org/subfields/2611","display_name":"Modeling and Simulation"},"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/T10410","display_name":"COVID-19 epidemiological studies","score":0.6333000063896179,"subfield":{"id":"https://openalex.org/subfields/2611","display_name":"Modeling and Simulation"},"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":0.16519999504089355,"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/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.0982000008225441,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/change-point-estimation","display_name":"change point estimation","score":0.9010000228881836},{"id":"https://openalex.org/keywords/longitudinal-data","display_name":"longitudinal data","score":0.8009999990463257},{"id":"https://openalex.org/keywords/model-comparison","display_name":"model comparison","score":0.43700000643730164}],"concepts":[{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"score":0.7199275493621826},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.7175189852714539},{"id":"https://openalex.org/C89623803","wikidata":"https://www.wikidata.org/wiki/Q12184","display_name":"Pandemic","level":5,"score":0.6554424166679382},{"id":"https://openalex.org/C2986587452","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical analysis","level":2,"score":0.560938835144043},{"id":"https://openalex.org/C3007834351","wikidata":"https://www.wikidata.org/wiki/Q82069695","display_name":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)","level":5,"score":0.4893772006034851},{"id":"https://openalex.org/C3006700255","wikidata":"https://www.wikidata.org/wiki/Q81068910","display_name":"2019-20 coronavirus outbreak","level":3,"score":0.48561492562294006},{"id":"https://openalex.org/C161191863","wikidata":"https://www.wikidata.org/wiki/Q199655","display_name":"Library science","level":1,"score":0.4373038709163666},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.4121451675891876},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.21214035153388977},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16074201464653015},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.13311317563056946},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12880375981330872},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.12410742044448853},{"id":"https://openalex.org/C159047783","wikidata":"https://www.wikidata.org/wiki/Q7215","display_name":"Virology","level":1,"score":0.08875530958175659},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C116675565","wikidata":"https://www.wikidata.org/wiki/Q3241045","display_name":"Outbreak","level":2,"score":0.0},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1111/rssa.12937","doi":"https://doi.org/10.1111/rssa.12937","is_oa":false,"landing_page_url":"https://doi.org/10.1111/rssa.12937","pdf_url":null,"source":{"id":"https://openalex.org/S185328345","display_name":"Journal of the Royal Statistical Society Series A (Statistics in Society)","issn_l":"0964-1998","issn":["0964-1998","1467-985X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","cwts-core","doyens","jufo-2","ki-jl-2","norway-2"],"host_organization":"https://openalex.org/P4310311763","host_organization_name":"Royal Statistical Society","host_organization_lineage":["https://openalex.org/P4310311763"],"host_organization_lineage_names":["Royal Statistical Society"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Royal Statistical Society Series A: Statistics in Society","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.5683000087738037}],"sustainable_development_goals_aurora":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.6899999976158142}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W3007810145","https://openalex.org/W3138615272","https://openalex.org/W4225731448"],"related_works":["https://openalex.org/W3036314732","https://openalex.org/W4205317059","https://openalex.org/W3009669391","https://openalex.org/W4382894326","https://openalex.org/W3198183218","https://openalex.org/W3081785542","https://openalex.org/W3171943759","https://openalex.org/W3176864053","https://openalex.org/W3084498529","https://openalex.org/W4206669628"],"abstract_inverted_index":{"We":[0],"congratulate":[1],"Prof.":[2,4,7],"Jiang,":[3],"Zhao":[5],"and":[6,12,51,55,61,69,78,115,133,159,169,273],"Shao":[8],"for":[9,75,127,149,166,270,290],"their":[10,201,294],"timely":[11],"thought-provoking":[13],"paper":[14,202],"on":[15,33,277],"modelling":[16],"the":[17,93,124,128,171,174,182,205,220,253,264,278,283,288],"COVID-19":[18,183,269],"infection":[19,184,254,266],"trajectory":[20],"using":[21,282],"a":[22,34,105,111,118,154],"piecewise":[23,94],"linear":[24,95],"quantile":[25,96],"trend":[26,97],"model.":[27,98],"A":[28],"novel":[29],"segmentation":[30],"algorithm":[31],"based":[32,276],"self-normalised":[35],"(SN)":[36],"test":[37],"statistic":[38],"is":[39,49,145,153,161,203,211,224],"proposed":[40,47],"to":[41,53,92,180,213,250],"estimate":[42],"multiple":[43,187],"change":[44,143,188,217,259],"points.":[45,189,218,260],"The":[46,82,135,190,296],"model":[48,84,137,176,181,194,198,209,222,235,280],"interpretable":[50,68],"robust":[52,70],"outliers":[54],"heteroscedasticity.":[56],"Zhong":[57],"et":[58,63],"al.":[59,64],"(2021)":[60,65],"Wan":[62],"developed":[66],"an":[67,89,139],"Multi-Kink":[71],"Quantile":[72],"Regression":[73],"(MKQR)":[74],"independent":[76],"data":[77,285],"longitudinal":[79,100],"data,":[80,101],"respectively.":[81],"MKQR":[83,136,175,221,279],"can":[85,177],"be":[86,110,117,178,214,248],"considered":[87],"as":[88,227],"alternative":[90],"method":[91],"In":[99],"let":[102],"Yij":[103],"denote":[104],"response":[106],"of":[107,142,156,193,208,268,302],"interest,":[108],"Xij":[109],"univariate":[112],"threshold":[113],"variable":[114],"Zij":[116],"p-dimensional":[119],"additional":[120],"covariates":[121,172],"vector":[122,155],"at":[123,216,258],"jth":[125],"observation":[126],"ith":[129],"subject,":[130],"where":[131,147],"j=1,2,\u2026,ni":[132],"i=1,2,\u22ef,n\u2060.":[134],"with":[138,186,197],"unknown":[140,232,239],"number":[141],"points":[144,158],"...":[146],"(a)+=aI(a>0)":[148],"any":[150],"a\u2208\u211d\u2060,":[151],"(\u03b41,\u2026,\u03b4m0)T":[152],"change/kink":[157],"m0":[160],"unknown.":[162],"By":[163],"letting":[164],"Xij=t/n":[165],"country":[167],"i":[168],"ignoring":[170],"Zij\u2060,":[173],"used":[179],"curves":[185,255,267],"main":[191],"difference":[192],"(D.1)":[195,210,223,281],"compared":[196],"(1)":[199,236],"in":[200,243,293],"that":[204,252],"regression":[206],"curve":[207],"required":[212],"continuous":[215,257],"Hence,":[219],"more":[225],"parsimonious":[226],"it":[228,246],"requires":[229],"estimating":[230],"m0+2":[231],"parameters":[233],"while":[234],"has":[237],"2m0":[238],"parameters.":[240],"As":[241],"observed":[242],"Figure":[244,261,291],"D.1":[245,262,292],"may":[247],"reasonable":[249],"assume":[251],"are":[256,304],"depicts":[263],"estimated":[265],"United":[271,274],"States":[272],"Kingdom":[275],"same":[284],"provided":[286],"by":[287],"authors":[289],"paper.":[295],"further":[297,306],"comparison":[298],"between":[299],"two":[300],"kinds":[301],"models":[303],"worth":[305],"being":[307],"investigated.":[308]},"counts_by_year":[{"year":2022,"cited_by_count":2}],"updated_date":"2026-09-24T07:57:37.273135","created_date":"2025-10-10T00:00:00"}
