{"id":"https://openalex.org/W4205548639","doi":"https://doi.org/10.3390/sym14020186","title":"Copula-Based Estimation Methods for a Common Mean Vector for Bivariate Meta-Analyses","display_name":"Copula-Based Estimation Methods for a Common Mean Vector for Bivariate Meta-Analyses","publication_year":2022,"publication_date":"2022-01-18","ids":{"openalex":"https://openalex.org/W4205548639","doi":"https://doi.org/10.3390/sym14020186"},"language":"en","primary_location":{"id":"doi:10.3390/sym14020186","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14020186","pdf_url":"https://www.mdpi.com/2073-8994/14/2/186/pdf?version=1642506220","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/14/2/186/pdf?version=1642506220","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016499245","display_name":"Jia\u2010Han Shih","orcid":null},"institutions":[{"id":"https://openalex.org/I4210141710","display_name":"Institute of Statistical Science, Academia Sinica","ror":"https://ror.org/044gv5910","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210141710","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jia-Han Shih","raw_affiliation_strings":["Institute of Statistical Science, Academia Sinica, Taipei 11529, Taiwan"],"affiliations":[{"raw_affiliation_string":"Institute of Statistical Science, Academia Sinica, Taipei 11529, Taiwan","institution_ids":["https://openalex.org/I4210141710"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040059343","display_name":"Yoshihiko Konno","orcid":null},"institutions":[{"id":"https://openalex.org/I29457043","display_name":"Japan Women's University","ror":"https://ror.org/04gpcyk21","country_code":"JP","type":"education","lineage":["https://openalex.org/I29457043"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshihiko Konno","raw_affiliation_strings":["Department of Mathematical and Physical Sciences, Japan Women\u2019s University, Tokyo 112-8681, Japan","Department of Mathematical and Physical Sciences, Japan Women's University, Tokyo 112-8681, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Mathematical and Physical Sciences, Japan Women\u2019s University, Tokyo 112-8681, Japan","institution_ids":["https://openalex.org/I29457043"]},{"raw_affiliation_string":"Department of Mathematical and Physical Sciences, Japan Women's University, Tokyo 112-8681, Japan","institution_ids":["https://openalex.org/I29457043"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014090405","display_name":"Yuan-Tsung Chang","orcid":"https://orcid.org/0000-0001-6929-165X"},"institutions":[{"id":"https://openalex.org/I91947458","display_name":"Mejiro University","ror":"https://ror.org/047wxqn68","country_code":"JP","type":"education","lineage":["https://openalex.org/I91947458"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuan-Tsung Chang","raw_affiliation_strings":["Department of Social Information, Mejiro University, Tokyo 161-8539, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Social Information, Mejiro University, Tokyo 161-8539, Japan","institution_ids":["https://openalex.org/I91947458"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020629689","display_name":"Takeshi Emura","orcid":"https://orcid.org/0000-0002-3904-4014"},"institutions":[{"id":"https://openalex.org/I105296287","display_name":"Kurume University","ror":"https://ror.org/057xtrt18","country_code":"JP","type":"education","lineage":["https://openalex.org/I105296287"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Takeshi Emura","raw_affiliation_strings":["Biostatistics Center, Kurume University, Kurume, Fukuoka 830-0011, Japan"],"affiliations":[{"raw_affiliation_string":"Biostatistics Center, Kurume University, Kurume, Fukuoka 830-0011, Japan","institution_ids":["https://openalex.org/I105296287"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5020629689"],"corresponding_institution_ids":["https://openalex.org/I105296287"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":4.4355,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.95586069,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"14","issue":"2","first_page":"186","last_page":"186"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.9797999858856201,"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/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.9797999858856201,"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":0.9621999859809875,"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/T11798","display_name":"Optimal Experimental Design Methods","score":0.9610000252723694,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"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/copula","display_name":"Copula (linguistics)","score":0.9541333913803101},{"id":"https://openalex.org/keywords/bivariate-analysis","display_name":"Bivariate analysis","score":0.9060036540031433},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.6381509304046631},{"id":"https://openalex.org/keywords/meta-analysis","display_name":"Meta-analysis","score":0.525848925113678},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5213088393211365},{"id":"https://openalex.org/keywords/joint-probability-distribution","display_name":"Joint probability distribution","score":0.4769400656223297},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4342659115791321},{"id":"https://openalex.org/keywords/multivariate-normal-distribution","display_name":"Multivariate normal distribution","score":0.4182211756706238},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.32524654269218445},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.24064594507217407}],"concepts":[{"id":"https://openalex.org/C17618745","wikidata":"https://www.wikidata.org/wiki/Q207509","display_name":"Copula (linguistics)","level":2,"score":0.9541333913803101},{"id":"https://openalex.org/C64341305","wikidata":"https://www.wikidata.org/wiki/Q4919225","display_name":"Bivariate analysis","level":2,"score":0.9060036540031433},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.6381509304046631},{"id":"https://openalex.org/C95190672","wikidata":"https://www.wikidata.org/wiki/Q815382","display_name":"Meta-analysis","level":2,"score":0.525848925113678},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5213088393211365},{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.4769400656223297},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4342659115791321},{"id":"https://openalex.org/C177384507","wikidata":"https://www.wikidata.org/wiki/Q1149000","display_name":"Multivariate normal distribution","level":3,"score":0.4182211756706238},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.32524654269218445},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.24064594507217407},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/sym14020186","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14020186","pdf_url":"https://www.mdpi.com/2073-8994/14/2/186/pdf?version=1642506220","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b50a33c17fb345b991c692a188327d10","is_oa":true,"landing_page_url":"https://doaj.org/article/b50a33c17fb345b991c692a188327d10","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry, Vol 14, Iss 2, p 186 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2073-8994/14/2/186/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/sym14020186","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/sym14020186","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14020186","pdf_url":"https://www.mdpi.com/2073-8994/14/2/186/pdf?version=1642506220","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4205548639.pdf","grobid_xml":"https://content.openalex.org/works/W4205548639.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W1457220277","https://openalex.org/W1460189015","https://openalex.org/W1910867164","https://openalex.org/W1923992966","https://openalex.org/W1963760643","https://openalex.org/W1977947020","https://openalex.org/W2009253656","https://openalex.org/W2015510128","https://openalex.org/W2025420088","https://openalex.org/W2026417450","https://openalex.org/W2046747497","https://openalex.org/W2054957279","https://openalex.org/W2075120110","https://openalex.org/W2080060609","https://openalex.org/W2083515875","https://openalex.org/W2102347194","https://openalex.org/W2105161819","https://openalex.org/W2113732482","https://openalex.org/W2117664464","https://openalex.org/W2127125241","https://openalex.org/W2129567559","https://openalex.org/W2137611062","https://openalex.org/W2201830033","https://openalex.org/W2403080995","https://openalex.org/W2734875222","https://openalex.org/W2775736374","https://openalex.org/W2789301122","https://openalex.org/W2791077373","https://openalex.org/W2794228672","https://openalex.org/W2804744026","https://openalex.org/W2916071171","https://openalex.org/W2921311622","https://openalex.org/W2931560430","https://openalex.org/W2943997241","https://openalex.org/W2955788542","https://openalex.org/W2997876558","https://openalex.org/W3009192602","https://openalex.org/W3020176950","https://openalex.org/W3035310783","https://openalex.org/W3088579130","https://openalex.org/W3104128392","https://openalex.org/W3156308486","https://openalex.org/W3158113069","https://openalex.org/W3205721448","https://openalex.org/W3206701744","https://openalex.org/W4205096937","https://openalex.org/W4233494161","https://openalex.org/W4249446031","https://openalex.org/W4252584470","https://openalex.org/W6677105531","https://openalex.org/W6678119076","https://openalex.org/W6744994289","https://openalex.org/W6757598146","https://openalex.org/W6779640607"],"related_works":["https://openalex.org/W2990837948","https://openalex.org/W3127236696","https://openalex.org/W2202466617","https://openalex.org/W2080551413","https://openalex.org/W2756923888","https://openalex.org/W2767176313","https://openalex.org/W4287838929","https://openalex.org/W2359012312","https://openalex.org/W2800558361","https://openalex.org/W3177005804"],"abstract_inverted_index":{"Traditional":[0],"bivariate":[1,5,10,35,45,77,96,161],"meta-analyses":[2],"adopt":[3],"the":[4,9,23,34,54,61,80,89,94,101,118,138,146,157,160],"normal":[6,11,36,55,162],"model.":[7,163],"As":[8,30],"distribution":[12],"produces":[13],"symmetric":[14,51],"dependence,":[15],"it":[16],"is":[17,85,107],"not":[18],"flexible":[19],"enough":[20],"to":[21,33,86,121,136,144],"describe":[22],"true":[24],"dependence":[25],"structure":[26],"of":[27,49,82,93,112,125,159],"real":[28,150],"meta-analyses.":[29,46],"an":[31],"alternative":[32],"model,":[37],"recent":[38],"papers":[39],"have":[40],"adopted":[41],"\u201ccopula\u201d":[42],"models":[43,66],"for":[44,99,154],"Copulas":[47],"consist":[48],"both":[50],"copulas":[52,59],"(e.g.,":[53,60],"copula)":[56],"and":[57,91],"asymmetric":[58],"Clayton":[62],"copula).":[63],"While":[64],"copula":[65,120],"are":[67,70,142,152],"promising,":[68],"there":[69],"only":[71],"a":[72,110,122,131],"few":[73],"studies":[74,116],"on":[75],"copula-based":[76,95],"meta-analysis.":[78],"Therefore,":[79],"goal":[81],"this":[83],"article":[84],"fully":[87],"develop":[88,130],"methodologies":[90],"theories":[92],"meta-analysis,":[97],"specifically":[98],"estimating":[100],"common":[102],"mean":[103],"vector.":[104],"This":[105],"work":[106],"regarded":[108],"as":[109],"generalization":[111],"our":[113],"previous":[114],"methodological/theoretical":[115],"under":[117],"FGM":[119],"broad":[123],"class":[124],"copulas.":[126],"In":[127],"addition,":[128],"we":[129],"new":[132],"R":[133],"package,":[134],"\u201cCommonMean.Copula\u201d,":[135],"implement":[137],"proposed":[139,147],"methods.":[140,148],"Simulations":[141],"performed":[143],"check":[145],"Two":[149],"dataset":[151],"analyzed":[153],"illustration,":[155],"demonstrating":[156],"insufficiency":[158]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":5}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
