{"id":"https://openalex.org/W4387374732","doi":"https://doi.org/10.1007/s11634-023-00560-8","title":"Generalized Cram\u00e9r\u2019s coefficient via f-divergence for contingency tables","display_name":"Generalized Cram\u00e9r\u2019s coefficient via f-divergence for contingency tables","publication_year":2023,"publication_date":"2023-10-05","ids":{"openalex":"https://openalex.org/W4387374732","doi":"https://doi.org/10.1007/s11634-023-00560-8"},"language":"en","primary_location":{"id":"doi:10.1007/s11634-023-00560-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11634-023-00560-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11634-023-00560-8.pdf","source":{"id":"https://openalex.org/S4210175730","display_name":"Advances in Data Analysis and Classification","issn_l":"1862-5347","issn":["1862-5347","1862-5355"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advances in Data Analysis and Classification","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11634-023-00560-8.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061648688","display_name":"Wataru Urasaki","orcid":"https://orcid.org/0000-0003-0155-4294"},"institutions":[{"id":"https://openalex.org/I161296585","display_name":"Tokyo University of Science","ror":"https://ror.org/05sj3n476","country_code":"JP","type":"education","lineage":["https://openalex.org/I161296585"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Wataru Urasaki","raw_affiliation_strings":["Department of Information Sciences, Tokyo University of Science, Noda City, Chiba, 278-8510, Japan"],"raw_orcid":"https://orcid.org/0000-0003-0155-4294","affiliations":[{"raw_affiliation_string":"Department of Information Sciences, Tokyo University of Science, Noda City, Chiba, 278-8510, Japan","institution_ids":["https://openalex.org/I161296585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058981124","display_name":"Tomoyuki Nakagawa","orcid":"https://orcid.org/0000-0001-5057-5927"},"institutions":[{"id":"https://openalex.org/I161296585","display_name":"Tokyo University of Science","ror":"https://ror.org/05sj3n476","country_code":"JP","type":"education","lineage":["https://openalex.org/I161296585"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomoyuki Nakagawa","raw_affiliation_strings":["Department of Information Sciences, Tokyo University of Science, Noda City, Chiba, 278-8510, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Sciences, Tokyo University of Science, Noda City, Chiba, 278-8510, Japan","institution_ids":["https://openalex.org/I161296585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007508793","display_name":"Tomotaka Momozaki","orcid":"https://orcid.org/0000-0001-6735-0804"},"institutions":[{"id":"https://openalex.org/I161296585","display_name":"Tokyo University of Science","ror":"https://ror.org/05sj3n476","country_code":"JP","type":"education","lineage":["https://openalex.org/I161296585"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomotaka Momozaki","raw_affiliation_strings":["Department of Information Sciences, Tokyo University of Science, Noda City, Chiba, 278-8510, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Sciences, Tokyo University of Science, Noda City, Chiba, 278-8510, Japan","institution_ids":["https://openalex.org/I161296585"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049149402","display_name":"Sadao Tomizawa","orcid":"https://orcid.org/0000-0002-2819-827X"},"institutions":[{"id":"https://openalex.org/I161296585","display_name":"Tokyo University of Science","ror":"https://ror.org/05sj3n476","country_code":"JP","type":"education","lineage":["https://openalex.org/I161296585"]},{"id":"https://openalex.org/I63030401","display_name":"Meisei University","ror":"https://ror.org/022yhjq53","country_code":"JP","type":"education","lineage":["https://openalex.org/I63030401"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Sadao Tomizawa","raw_affiliation_strings":["Department of Information Science, Meisei University, Hino City, Tokyo, 191-8506, Japan","Department of Information Sciences, Tokyo University of Science, Noda City, Chiba, 278-8510, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Science, Meisei University, Hino City, Tokyo, 191-8506, Japan","institution_ids":["https://openalex.org/I63030401"]},{"raw_affiliation_string":"Department of Information Sciences, Tokyo University of Science, Noda City, Chiba, 278-8510, Japan","institution_ids":["https://openalex.org/I161296585"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5061648688"],"corresponding_institution_ids":["https://openalex.org/I161296585"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":0.6586,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.72434566,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"18","issue":"4","first_page":"893","last_page":"910"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.982200026512146,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.982200026512146,"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/T12114","display_name":"Sensory Analysis and Statistical Methods","score":0.9713000059127808,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9664999842643738,"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/contingency-table","display_name":"Contingency table","score":0.9730637669563293},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.7905110120773315},{"id":"https://openalex.org/keywords/bivariate-analysis","display_name":"Bivariate analysis","score":0.6924594044685364},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.6582832336425781},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5595965385437012},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.5272173881530762},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.48058366775512695},{"id":"https://openalex.org/keywords/contingency","display_name":"Contingency","score":0.469672292470932},{"id":"https://openalex.org/keywords/pearson-product-moment-correlation-coefficient","display_name":"Pearson product-moment correlation coefficient","score":0.42905694246292114},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.42772746086120605},{"id":"https://openalex.org/keywords/kullback\u2013leibler-divergence","display_name":"Kullback\u2013Leibler divergence","score":0.41447341442108154},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3258345127105713},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3213834762573242},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.23011896014213562}],"concepts":[{"id":"https://openalex.org/C91998498","wikidata":"https://www.wikidata.org/wiki/Q1541178","display_name":"Contingency table","level":2,"score":0.9730637669563293},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.7905110120773315},{"id":"https://openalex.org/C64341305","wikidata":"https://www.wikidata.org/wiki/Q4919225","display_name":"Bivariate analysis","level":2,"score":0.6924594044685364},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.6582832336425781},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5595965385437012},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.5272173881530762},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.48058366775512695},{"id":"https://openalex.org/C97508593","wikidata":"https://www.wikidata.org/wiki/Q1359069","display_name":"Contingency","level":2,"score":0.469672292470932},{"id":"https://openalex.org/C55078378","wikidata":"https://www.wikidata.org/wiki/Q1136628","display_name":"Pearson product-moment correlation coefficient","level":2,"score":0.42905694246292114},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.42772746086120605},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.41447341442108154},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3258345127105713},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3213834762573242},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.23011896014213562},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s11634-023-00560-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11634-023-00560-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11634-023-00560-8.pdf","source":{"id":"https://openalex.org/S4210175730","display_name":"Advances in Data Analysis and Classification","issn_l":"1862-5347","issn":["1862-5347","1862-5355"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advances in Data Analysis and Classification","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:spr:advdac:v:18:y:2024:i:4:d:10.1007_s11634-023-00560-8","is_oa":false,"landing_page_url":"http://link.springer.com/10.1007/s11634-023-00560-8","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s11634-023-00560-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11634-023-00560-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11634-023-00560-8.pdf","source":{"id":"https://openalex.org/S4210175730","display_name":"Advances in Data Analysis and Classification","issn_l":"1862-5347","issn":["1862-5347","1862-5355"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advances in Data Analysis and Classification","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5002487236","display_name":null,"funder_award_id":"JP20K03756","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387374732.pdf"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W107085514","https://openalex.org/W152055444","https://openalex.org/W603636824","https://openalex.org/W1516900628","https://openalex.org/W1526778215","https://openalex.org/W1585397645","https://openalex.org/W1966236948","https://openalex.org/W1969275591","https://openalex.org/W1980630966","https://openalex.org/W1997469190","https://openalex.org/W2006866327","https://openalex.org/W2016726176","https://openalex.org/W2017262052","https://openalex.org/W2028549423","https://openalex.org/W2036435423","https://openalex.org/W2051317694","https://openalex.org/W2055309977","https://openalex.org/W2099554398","https://openalex.org/W2159205977","https://openalex.org/W2159902206","https://openalex.org/W2321731070","https://openalex.org/W2518143623","https://openalex.org/W2729518911","https://openalex.org/W2772202208","https://openalex.org/W3025698313","https://openalex.org/W3102159535","https://openalex.org/W3123612829","https://openalex.org/W4206202898","https://openalex.org/W4232359393","https://openalex.org/W4245672031","https://openalex.org/W4255783720","https://openalex.org/W4281264527","https://openalex.org/W4294841944","https://openalex.org/W4301006716","https://openalex.org/W4307028305"],"related_works":["https://openalex.org/W2168242335","https://openalex.org/W3001524306","https://openalex.org/W4206843815","https://openalex.org/W1500592506","https://openalex.org/W2327075898","https://openalex.org/W2996891946","https://openalex.org/W2945555665","https://openalex.org/W3165869498","https://openalex.org/W2082307124","https://openalex.org/W2389190814"],"abstract_inverted_index":{"Abstract":[0],"Various":[1],"measures":[2,44,62,178],"in":[3,22,69,102,157,183,191],"two-way":[4],"contingency":[5,23,70,103,159,193],"table":[6],"analysis":[7],"have":[8],"been":[9],"proposed":[10,29,177],"to":[11],"express":[12],"the":[13,37,46,55,66,87,90,98,123,135,149,152,158,167,180,192],"strength":[14,99],"of":[15,65,74,89,100,148,188],"association":[16,67,101,150],"between":[17,151,175],"row":[18,153],"and":[19,154,179],"column":[20,155],"variables":[21,156,190],"tables.":[24,71,104,194],"Tomizawa":[25],"et":[26],"al.":[27],"(2004)":[28],"more":[30],"general":[31],"measures,":[32],"including":[33],"Cram\u00e9r\u2019s":[34],"coefficient,":[35],"using":[36,45,115],"power-divergence.":[38,56],"In":[39],"this":[40,106],"paper,":[41],"we":[42,108,127,143],"propose":[43],"f":[47,91],"-divergence":[48,92],"that":[49,79,85,118],"has":[50,93,119],"a":[51,80,83,112,116,132,173,184],"wider":[52],"class":[53],"than":[54],"Unlike":[57],"statistical":[58],"hypothesis":[59],"tests,":[60],"these":[61],"provide":[63],"quantification":[64],"structure":[68],"The":[72],"contribution":[73],"our":[75,176],"study":[76],"is":[77],"proving":[78],"measure":[81,114,133],"applying":[82,134],"function":[84],"satisfies":[86],"condition":[88],"desirable":[94],"properties":[95,121],"for":[96,122],"measuring":[97],"With":[105],"contribution,":[107],"can":[109,144],"easily":[110],"construct":[111],"new":[113],"divergence":[117],"essential":[120],"analyst.":[124],"For":[125],"example,":[126],"conducted":[128],"numerical":[129],"experiments":[130],"with":[131,166],"$$\\theta$$":[136],"<mml:math":[137],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\">":[138],"<mml:mi>\u03b8</mml:mi>":[139],"</mml:math>":[140],"-divergence.":[141],"Furthermore,":[142],"give":[145],"further":[146],"interpretation":[147],"table,":[160],"which":[161],"could":[162],"not":[163],"be":[164],"obtained":[165],"conventional":[168],"one.":[169],"We":[170],"also":[171],"show":[172],"relationship":[174],"correlation":[181],"coefficient":[182],"bivariate":[185],"normal":[186],"distribution":[187],"latent":[189]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}