{"id":"https://openalex.org/W2025254686","doi":"https://doi.org/10.1080/01621459.1989.10478781","title":"Multivariate Methods for Clustered Binary Data with More Than One Level of Nesting","display_name":"Multivariate Methods for Clustered Binary Data with More Than One Level of Nesting","publication_year":1989,"publication_date":"1989-06-01","ids":{"openalex":"https://openalex.org/W2025254686","doi":"https://doi.org/10.1080/01621459.1989.10478781","mag":"2025254686"},"language":"en","primary_location":{"id":"doi:10.1080/01621459.1989.10478781","doi":"https://doi.org/10.1080/01621459.1989.10478781","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01621459.1989.10478781","pdf_url":null,"source":{"id":"https://openalex.org/S4394736638","display_name":"Journal of the American Statistical Association","issn_l":"0162-1459","issn":["0162-1459","1537-274X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a-star","anvur-class-a","anvur-scientific","cwts-core","dongbi-a","doyens","jufo-3","ki-jl-3","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Statistical Association","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/A5089191285","display_name":"BERNARD A. ROSNER","orcid":"https://orcid.org/0000-0001-6907-0056","observed_orcids":["https://orcid.org/0000-0001-6907-0056"]},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Bernard Rosner","raw_affiliation_strings":["Department of Preventive Medicine and Clinical Epidemiology, and Chief Biostatistician, Channing Laboratory, Harvard Medical School, Boston, MA, 02115, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Preventive Medicine and Clinical Epidemiology, and Chief Biostatistician, Channing Laboratory, Harvard Medical School, Boston, MA, 02115, USA","institution_ids":["https://openalex.org/I136199984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5089191285"],"corresponding_institution_ids":["https://openalex.org/I136199984"],"apc_list":null,"apc_paid":null,"fwci":6.1342,"has_fulltext":false,"cited_by_count":70,"citation_normalized_percentile":{"value":0.96790037,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":"84","issue":"406","first_page":"373","last_page":"373"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9717000126838684,"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":0.9717000126838684,"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/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.007199999876320362,"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/T14374","display_name":"Statistical Methods in Epidemiology","score":0.0038999998942017555,"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/clustered-binary-data","display_name":"clustered binary data","score":0.9670000076293945},{"id":"https://openalex.org/keywords/beta-binomial-distribution","display_name":"beta-binomial distribution","score":0.8420000076293945},{"id":"https://openalex.org/keywords/intracluster-correlation","display_name":"intra-cluster correlation","score":0.6129999756813049},{"id":"https://openalex.org/keywords/multivariate-logistic-regression","display_name":"multivariate logistic regression","score":0.4050000011920929}],"concepts":[{"id":"https://openalex.org/C114494560","wikidata":"https://www.wikidata.org/wiki/Q4914493","display_name":"Binomial regression","level":3,"score":0.6815889477729797},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.6705421209335327},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.6690496206283569},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.6231417655944824},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6140584349632263},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.5710388422012329},{"id":"https://openalex.org/C41054675","wikidata":"https://www.wikidata.org/wiki/Q185547","display_name":"Binomial distribution","level":2,"score":0.5287242531776428},{"id":"https://openalex.org/C199335787","wikidata":"https://www.wikidata.org/wiki/Q743364","display_name":"Negative binomial distribution","level":3,"score":0.48917725682258606},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.48734721541404724},{"id":"https://openalex.org/C2776937656","wikidata":"https://www.wikidata.org/wiki/Q2229669","display_name":"Nesting (process)","level":2,"score":0.4605952501296997},{"id":"https://openalex.org/C2781315470","wikidata":"https://www.wikidata.org/wiki/Q193623","display_name":"Binomial (polynomial)","level":2,"score":0.4523584842681885},{"id":"https://openalex.org/C2779190172","wikidata":"https://www.wikidata.org/wiki/Q4913888","display_name":"Binary data","level":3,"score":0.44818592071533203},{"id":"https://openalex.org/C165480597","wikidata":"https://www.wikidata.org/wiki/Q307557","display_name":"Beta-binomial distribution","level":4,"score":0.44782555103302},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.44588837027549744},{"id":"https://openalex.org/C27403532","wikidata":"https://www.wikidata.org/wiki/Q5532474","display_name":"Generalized estimating equation","level":2,"score":0.44555947184562683},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.43153366446495056},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.242156982421875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.17871472239494324},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/01621459.1989.10478781","doi":"https://doi.org/10.1080/01621459.1989.10478781","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01621459.1989.10478781","pdf_url":null,"source":{"id":"https://openalex.org/S4394736638","display_name":"Journal of the American Statistical Association","issn_l":"0162-1459","issn":["0162-1459","1537-274X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a-star","anvur-class-a","anvur-scientific","cwts-core","dongbi-a","doyens","jufo-3","ki-jl-3","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Statistical Association","raw_type":"journal-article"},{"id":"doi:10.2307/2289920","doi":"https://doi.org/10.2307/2289920","is_oa":false,"landing_page_url":"https://doi.org/10.2307/2289920","pdf_url":null,"source":{"id":"https://openalex.org/S4394736638","display_name":"Journal of the American Statistical Association","issn_l":"0162-1459","issn":["0162-1459","1537-274X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a-star","anvur-class-a","anvur-scientific","cwts-core","dongbi-a","doyens","jufo-3","ki-jl-3","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Statistical Association","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}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W90334641","https://openalex.org/W2015981771","https://openalex.org/W2017085212","https://openalex.org/W2020712165","https://openalex.org/W2024085858","https://openalex.org/W2026483009","https://openalex.org/W2042328479","https://openalex.org/W2049742986","https://openalex.org/W2063590966","https://openalex.org/W2064107843","https://openalex.org/W2106596699","https://openalex.org/W2149860264","https://openalex.org/W2287851705","https://openalex.org/W2320670580","https://openalex.org/W2797829289","https://openalex.org/W4298407707"],"related_works":["https://openalex.org/W2080835830","https://openalex.org/W2066778178","https://openalex.org/W2320670580","https://openalex.org/W2081606767","https://openalex.org/W1989599223","https://openalex.org/W2086375955","https://openalex.org/W2026483009","https://openalex.org/W2130448352","https://openalex.org/W2313619083","https://openalex.org/W1923431858"],"abstract_inverted_index":{"Clustered":[0],"data":[1,16,168],"occur":[2],"frequently":[3],"in":[4,89,127,171,238],"statistical":[5],"practice.":[6],"In":[7,24,51,145,205],"some":[8],"areas":[9],"of":[10,37,40,66,92,102,117,156,186,198,208,229,247,260,268],"application,":[11,166],"such":[12,30],"as":[13,31,123],"ophthalmology,":[14,128],"clustered":[15],"are":[17,34,139,169,270],"the":[18,22,38,64,75,90,130,133,136,140,180,183,195,206,210,221,245],"rule":[19],"rather":[20],"than":[21,226,265],"exception.":[23],"this":[25,146,148],"setting,":[26,241],"standard":[27],"multivariate":[28],"methods":[29],"logistic":[32,56,98],"regression":[33,57,240],"invalid,":[35],"because":[36],"lack":[39],"independence":[41],"among":[42,77,188],"outcomes":[43],"for":[44,63,74,100,106,244,255],"individual":[45,137],"sample":[46],"points":[47],"within":[48,79,142,190,202],"a":[49,54,80,86,143,153,191,203,215,239],"cluster.":[50,81,144],"Rosner":[52],"(1984),":[53],"polychotomous":[55],"model":[58,83,88,99,149,160,178,211],"was":[59],"presented":[60],"to":[61,85,95,152,177,224,242,263],"control":[62],"effect":[65],"both":[67],"cluster":[68,134],"and":[69,94,105,135,174,193,250],"individual-specific":[70],"covariates":[71,252],"while":[72,253],"accounting":[73],"correlation":[76,111,119,181,256],"units":[78,141,173],"This":[82,159],"reduces":[84],"beta-binomial":[87,217,222,233],"absence":[91,207],"covariates,":[93,209],"an":[96,164],"ordinary":[97],"clusters":[101,108],"size":[103],"1":[104,115],"larger":[107],"when":[109],"no":[110],"is":[112,121,124,132,150,161,212,235],"present.":[113],"A":[114],"level":[116,155,185,197,228,259],"nesting":[118,157,187,199,269],"structure":[120],"assumed,":[122],"typically":[125],"found":[126],"where":[129,167],"person":[131],"eyes":[138,201],"article,":[147],"generalized":[151],"2":[154],"structure.":[158],"motivated":[162],"by":[163,214],"ophthalmologic":[165],"collected":[170],"family":[172],"one":[175,227],"wishes":[176],"simultaneously":[179],"at":[182,194,257],"first":[184],"persons":[189],"family,":[192],"second":[196],"between":[200],"person.":[204],"characterized":[213],"compound":[216,232],"distribution":[218,223,234],"that":[219],"generalizes":[220],"more":[225,264],"nesting.":[230,261],"The":[231],"then":[236],"augmented":[237],"allow":[243],"presence":[246],"family-,":[248],"person-,":[249],"eye-specific":[251],"controlling":[254],"each":[258],"Extensions":[262],"two":[266],"levels":[267],"also":[271],"considered.":[272]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1}],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2016-06-24T00:00:00"}
