{"id":"https://openalex.org/W6902298818","doi":"https://doi.org/10.6084/m9.figshare.21834258","title":"A Correlated Network Scale-Up Model: Finding the Connection Between Subpopulations","display_name":"A Correlated Network Scale-Up Model: Finding the Connection Between Subpopulations","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W6902298818","doi":"https://doi.org/10.6084/m9.figshare.21834258"},"language":"en","primary_location":{"id":"pmh:oai:figshare.com:article/21834258","doi":null,"is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/A_Correlated_Network_Scale-up_Model_Finding_the_Connection_Between_Subpopulations/21834258","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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":"","raw_type":"Text"},"volume":null,"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/journal_contribution/A_Correlated_Network_Scale-up_Model_Finding_the_Connection_Between_Subpopulations/21834258","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071528990","display_name":"Ian Laga","orcid":"https://orcid.org/0000-0002-5164-4856","observed_orcids":["https://orcid.org/0000-0002-5164-4856"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Laga, Ian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010808240","display_name":"Le Bao","orcid":"https://orcid.org/0000-0003-0191-5918","observed_orcids":["https://orcid.org/0000-0003-0191-5918"]},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bao, Le","raw_affiliation_strings":["Pennsylvania State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pennsylvania State University","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080019599","display_name":"Xiaoyue Maggie Niu","orcid":"https://orcid.org/0000-0003-3384-7446","observed_orcids":["https://orcid.org/0000-0003-3384-7446"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Niu, Xiaoyue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24917722,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T13546","display_name":"Census and Population Estimation","score":0.5346999764442444,"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/T13546","display_name":"Census and Population Estimation","score":0.5346999764442444,"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/T13030","display_name":"Survey Sampling and Estimation Techniques","score":0.39089998602867126,"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/T11539","display_name":"Survey Methodology and Nonresponse","score":0.03920000046491623,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/network-size-estimation","display_name":"network size estimation","score":0.5799999833106995},{"id":"https://openalex.org/keywords/hard-to-reach-populations","display_name":"hard-to-reach populations","score":0.8159999847412109},{"id":"https://openalex.org/keywords/female-sex-workers","display_name":"female sex workers","score":0.9129999876022339},{"id":"https://openalex.org/keywords/hiv","display_name":"HIV","score":0.5139999985694885},{"id":"https://openalex.org/keywords/ukraine","display_name":"Ukraine","score":0.3880000114440918},{"id":"https://openalex.org/keywords/marginalized-communities","display_name":"marginalized communities","score":0.4399999976158142}],"concepts":[{"id":"https://openalex.org/C2776640315","wikidata":"https://www.wikidata.org/wiki/Q7315941","display_name":"Respondent","level":2,"score":0.7228000164031982},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5300999879837036},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4948999881744385},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4699000120162964},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.46480000019073486},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.45899999141693115},{"id":"https://openalex.org/C90329073","wikidata":"https://www.wikidata.org/wiki/Q914232","display_name":"Ask price","level":2,"score":0.45840001106262207},{"id":"https://openalex.org/C2776035688","wikidata":"https://www.wikidata.org/wiki/Q1606558","display_name":"Affect (linguistics)","level":2,"score":0.45010000467300415},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.40529999136924744},{"id":"https://openalex.org/C3013748606","wikidata":"https://www.wikidata.org/wiki/Q15787","display_name":"Human immunodeficiency virus (HIV)","level":2,"score":0.3937000036239624},{"id":"https://openalex.org/C91682802","wikidata":"https://www.wikidata.org/wiki/Q620538","display_name":"Multidimensional scaling","level":2,"score":0.3889999985694885},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.38109999895095825},{"id":"https://openalex.org/C13355873","wikidata":"https://www.wikidata.org/wiki/Q2920850","display_name":"Connection (principal bundle)","level":2,"score":0.36500000953674316},{"id":"https://openalex.org/C53059260","wikidata":"https://www.wikidata.org/wiki/Q374758","display_name":"Multilevel model","level":2,"score":0.3490000069141388},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3402000069618225},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3230000138282776},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.3149000108242035},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.3125999867916107},{"id":"https://openalex.org/C4727928","wikidata":"https://www.wikidata.org/wiki/Q17164759","display_name":"Social network (sociolinguistics)","level":3,"score":0.3098999857902527},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.3084999918937683},{"id":"https://openalex.org/C198477413","wikidata":"https://www.wikidata.org/wiki/Q7647069","display_name":"Survey data collection","level":2,"score":0.30720001459121704},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.30559998750686646},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.304500013589859},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30410000681877136},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2992999851703644},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.2955999970436096},{"id":"https://openalex.org/C2988224531","wikidata":"https://www.wikidata.org/wiki/Q20830730","display_name":"Network structure","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.2906000018119812},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.2865999937057495},{"id":"https://openalex.org/C2776441110","wikidata":"https://www.wikidata.org/wiki/Q1436628","display_name":"Randomized response","level":3,"score":0.27459999918937683},{"id":"https://openalex.org/C137753397","wikidata":"https://www.wikidata.org/wiki/Q2434424","display_name":"Network science","level":3,"score":0.27410000562667847},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25999999046325684},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.2540999948978424}],"mesh":[],"locations_count":4,"locations":[{"id":"pmh:oai:figshare.com:article/21834258","doi":null,"is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/A_Correlated_Network_Scale-up_Model_Finding_the_Connection_Between_Subpopulations/21834258","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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":"","raw_type":"Text"},{"id":"doi:10.6084/m9.figshare.21834258","doi":"https://doi.org/10.6084/m9.figshare.21834258","is_oa":true,"landing_page_url":"https://doi.org/10.6084/m9.figshare.21834258","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},{"id":"doi:10.6084/m9.figshare.21834258.v1","doi":"https://doi.org/10.6084/m9.figshare.21834258.v1","is_oa":true,"landing_page_url":"https://doi.org/10.6084/m9.figshare.21834258.v1","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},{"id":"doi:10.6084/m9.figshare.21834258.v2","doi":"https://doi.org/10.6084/m9.figshare.21834258.v2","is_oa":true,"landing_page_url":"https://doi.org/10.6084/m9.figshare.21834258.v2","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/21834258","doi":null,"is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/A_Correlated_Network_Scale-up_Model_Finding_the_Connection_Between_Subpopulations/21834258","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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":"","raw_type":"Text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.4000000059604645},{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.4000000059604645}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3111357448","https://openalex.org/W4376872848","https://openalex.org/W1573714765","https://openalex.org/W2074388851","https://openalex.org/W2187737304","https://openalex.org/W7154975096","https://openalex.org/W2970287667","https://openalex.org/W2079555253","https://openalex.org/W2308135293","https://openalex.org/W3109805872"],"abstract_inverted_index":{"Aggregated":[0],"Relational":[1],"Data":[2],"(ARD),":[3],"formed":[4],"from":[5,41,89,194,201],"\u201cHow":[6],"many":[7],"X\u2019s":[8],"do":[9],"you":[10],"know?\u201d":[11],"questions,":[12],"is":[13,32,56,127,191],"a":[14,39,107,118,123,134],"powerful":[15],"tool":[16],"for":[17,58,237],"learning":[18],"important":[19],"network":[20,24,174,179],"characteristics":[21,183],"with":[22],"incomplete":[23],"data.":[25],"Compared":[26],"to":[27,50,70,77,92,142,170,198,209],"traditional":[28],"survey":[29],"methods,":[30],"ARD":[31,88,109],"attractive":[33],"as":[34],"it":[35],"does":[36,46],"not":[37,47],"require":[38],"sample":[40],"the":[42,80,94,139,158,165,177,215,231],"target":[43],"population":[44],"and":[45,114,121,188,217,223],"ask":[48],"respondents":[49,91,186],"self-reveal":[51],"their":[52,72],"own":[53],"status.":[54,73],"This":[55],"helpful":[57],"studying":[59],"hard-to-reach":[60],"populations":[61],"like":[62],"female":[63],"sex":[64],"workers":[65],"who":[66,185],"may":[67],"be":[68],"hesitant":[69],"reveal":[71],"From":[74],"December":[75],"2008":[76],"February":[78],"2009,":[79],"Kiev":[81],"International":[82],"Institute":[83],"of":[84,96,150,153],"Sociology":[85],"(KIIS)":[86],"collected":[87],"10,866":[90],"estimate":[93],"size":[95,148],"HIV-related":[97],"groups":[98],"in":[99,117,162,230],"Ukraine.":[100,163],"To":[101],"analyze":[102],"this":[103,238],"data,":[104],"we":[105],"propose":[106],"new":[108,135],"model":[110,167,222],"which":[111],"incorporates":[112],"respondent":[113],"group":[115,196],"covariates":[116],"regression":[119],"framework":[120],"includes":[122],"bias":[124],"term":[125],"that":[126],"correlated":[128],"between":[129],"groups.":[130,203],"We":[131],"also":[132],"introduce":[133],"scaling":[136],"procedure":[137],"using":[138],"correlation":[140],"structure":[141],"further":[143],"reduce":[144],"biases.":[145],"The":[146],"resulting":[147],"estimates":[149],"those":[151],"most-at-risk":[152],"HIV":[154,159],"infection":[155],"can":[156,206],"improve":[157],"response":[160],"efficiency":[161],"Additionally,":[164],"proposed":[166,221],"allows":[168],"us":[169],"better":[171,210],"understand":[172],"two":[173],"features":[175,205],"without":[176],"full":[178],"data:":[180],"(a)":[181],"What":[182],"affect":[184],"know,":[187],"(b)":[189],"How":[190],"knowing":[192,199],"someone":[193],"one":[195],"related":[197],"people":[200],"other":[202],"These":[204],"allow":[207],"researchers":[208],"recruit":[211],"marginalized":[212],"individuals":[213],"into":[214],"prevention":[216],"treatment":[218],"programs.":[219],"Our":[220],"several":[224],"existing":[225],"NSUM":[226],"models":[227],"are":[228,240],"implemented":[229],"networkscaleup":[232],"R":[233],"package.":[234],"Supplementary":[235],"materials":[236],"article":[239],"available":[241],"online.":[242]},"counts_by_year":[],"updated_date":"2026-10-14T16:39:01.820549","created_date":"2025-10-10T00:00:00"}
