{"id":"https://openalex.org/W89797823","doi":null,"title":"NONPARAMETRIC METHODS IN COMPARING TWO CORRELATED ROC CURVES","display_name":"NONPARAMETRIC METHODS IN COMPARING TWO CORRELATED ROC CURVES","publication_year":2005,"publication_date":"2005-09-13","ids":{"openalex":"https://openalex.org/W89797823","mag":"89797823"},"language":"en","primary_location":{"id":"pmh:oai:d-scholarship.pitt.edu:8697","doi":null,"is_oa":true,"landing_page_url":"https://d-scholarship.pitt.edu/8697/1/Bandos_A_2005_PhD_dissertation.pdf","pdf_url":"http://d-scholarship.pitt.edu/8697/1/Bandos_A_2005_PhD_dissertation.pdf","source":{"id":"https://openalex.org/S4306402372","display_name":"D-Scholarship@Pitt (University of Pittsburgh)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I170201317","host_organization_name":"University of Pittsburgh","host_organization_lineage":["https://openalex.org/I170201317"],"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":"PeerReviewed"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://d-scholarship.pitt.edu/8697/1/Bandos_A_2005_PhD_dissertation.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031316574","display_name":"Andriy I. Bandos","orcid":"https://orcid.org/0000-0001-5629-1415","observed_orcids":["https://orcid.org/0000-0001-5629-1415"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Andriy I. Bandos","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-5629-1415","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5031316574"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3365,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.81670884,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.3596000075340271,"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"}},"topics":[{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.3596000075340271,"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"}},{"id":"https://openalex.org/T14374","display_name":"Statistical Methods in Epidemiology","score":0.28780001401901245,"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/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.03849999979138374,"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/roc-curve","display_name":"ROC curve","score":0.6919999718666077},{"id":"https://openalex.org/keywords/nonparametric-tests","display_name":"nonparametric tests","score":0.8199999928474426},{"id":"https://openalex.org/keywords/matched-pair-design","display_name":"paired design","score":0.6340000033378601},{"id":"https://openalex.org/keywords/diagnostic-test-comparison","display_name":"diagnostic test comparison","score":0.7649999856948853},{"id":"https://openalex.org/keywords/area-under-the-roc-curve","display_name":"area under the ROC curve","score":0.8899999856948853},{"id":"https://openalex.org/keywords/delong-test","display_name":"DeLong test","score":0.8899999856948853},{"id":"https://openalex.org/keywords/permutation-tests","display_name":"permutation tests","score":0.9409999847412109},{"id":"https://openalex.org/keywords/discordance","display_name":"discordance","score":0.871999979019165},{"id":"https://openalex.org/keywords/small-sample-properties","display_name":"small sample properties","score":0.8259999752044678},{"id":"https://openalex.org/keywords/diagnostic-accuracy","display_name":"diagnostic accuracy","score":0.7409999966621399}],"concepts":[{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.9090077877044678},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.7580534815788269},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5053787231445312},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4823314845561981},{"id":"https://openalex.org/C21308566","wikidata":"https://www.wikidata.org/wiki/Q7169365","display_name":"Permutation (music)","level":2,"score":0.4661703407764435},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.450603723526001},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4467525780200958},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36844855546951294},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3635069727897644},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3517186939716339},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3209803104400635},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:d-scholarship.pitt.edu:8697","doi":null,"is_oa":true,"landing_page_url":"https://d-scholarship.pitt.edu/8697/1/Bandos_A_2005_PhD_dissertation.pdf","pdf_url":"http://d-scholarship.pitt.edu/8697/1/Bandos_A_2005_PhD_dissertation.pdf","source":{"id":"https://openalex.org/S4306402372","display_name":"D-Scholarship@Pitt (University of Pittsburgh)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I170201317","host_organization_name":"University of Pittsburgh","host_organization_lineage":["https://openalex.org/I170201317"],"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":"PeerReviewed"},{"id":"mag:89797823","doi":null,"is_oa":false,"landing_page_url":"http://d-scholarship.pitt.edu/8697/","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:d-scholarship.pitt.edu:8697","doi":null,"is_oa":true,"landing_page_url":"https://d-scholarship.pitt.edu/8697/1/Bandos_A_2005_PhD_dissertation.pdf","pdf_url":"http://d-scholarship.pitt.edu/8697/1/Bandos_A_2005_PhD_dissertation.pdf","source":{"id":"https://openalex.org/S4306402372","display_name":"D-Scholarship@Pitt (University of Pittsburgh)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I170201317","host_organization_name":"University of Pittsburgh","host_organization_lineage":["https://openalex.org/I170201317"],"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":"PeerReviewed"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306085","display_name":"U.S. Department of Health and Human Services","ror":"https://ror.org/033jnv181"},{"id":"https://openalex.org/F4320310174","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305"},{"id":"https://openalex.org/F4320337363","display_name":"National Institute of Biomedical Imaging and Bioengineering","ror":"https://ror.org/00372qc85"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W89797823.pdf","grobid_xml":"https://content.openalex.org/works/W89797823.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W26510586","https://openalex.org/W1509445416","https://openalex.org/W1515026043","https://openalex.org/W1963582808","https://openalex.org/W1965902853","https://openalex.org/W1968114652","https://openalex.org/W1990534247","https://openalex.org/W1995945562","https://openalex.org/W1997739284","https://openalex.org/W2007723454","https://openalex.org/W2008830672","https://openalex.org/W2009618221","https://openalex.org/W2011748207","https://openalex.org/W2029489318","https://openalex.org/W2035950812","https://openalex.org/W2045554152","https://openalex.org/W2049172236","https://openalex.org/W2049549441","https://openalex.org/W2051269613","https://openalex.org/W2057335587","https://openalex.org/W2065230098","https://openalex.org/W2066886737","https://openalex.org/W2068656389","https://openalex.org/W2069401973","https://openalex.org/W2070595900","https://openalex.org/W2073383890","https://openalex.org/W2077788206","https://openalex.org/W2084413241","https://openalex.org/W2084656440","https://openalex.org/W2095485540","https://openalex.org/W2097841139","https://openalex.org/W2108023739","https://openalex.org/W2117897510","https://openalex.org/W2119029887","https://openalex.org/W2139372732","https://openalex.org/W2157825442","https://openalex.org/W2328176404","https://openalex.org/W2983601212","https://openalex.org/W3023299791"],"related_works":["https://openalex.org/W3108624078","https://openalex.org/W2108023739","https://openalex.org/W2328176404","https://openalex.org/W2026689190","https://openalex.org/W2977434218","https://openalex.org/W2172181348","https://openalex.org/W2110471281","https://openalex.org/W4213310372","https://openalex.org/W3033233391","https://openalex.org/W2057008822"],"abstract_inverted_index":{"Receiver":[0],"Operating":[1],"Characteristic":[2],"(ROC)":[3],"analysis":[4],"is":[5,22,84],"one":[6],"of":[7,17,29,56,81,88,109,140,206,221],"the":[8,54,85,107,123,137,141,161,164,199,204],"most":[9],"widely":[10],"used":[11,24],"methods":[12,36],"for":[13,69,73,106,129,156,180],"summarizing":[14],"intrinsic":[15],"properties":[16,55,139],"a":[18,50,63,74,94,100,188,210],"diagnostic":[19,30,57,158],"system,":[20],"and":[21,27,59,66,150,178,195],"often":[23],"in":[25,41,93,218],"evaluation":[26],"comparison":[28],"technologies,":[31],"practices":[32],"or":[33,71,77],"systems.":[34],"These":[35],"play":[37],"an":[38,175,181,192],"important":[39],"role":[40],"public":[42],"health":[43],"since":[44],"they":[45],"enable":[46],"researchers":[47],"to":[48,61,125,198],"achieve":[49],"greater":[51],"insight":[52],"into":[53],"tests":[58,103],"eventually":[60],"identify":[62],"more":[64,126],"appropriate":[65],"beneficial":[67],"procedure":[68],"diagnosing":[70],"screening":[72],"specific":[75],"disease":[76],"condition.":[78],"The":[79,167],"topic":[80],"this":[82,119,133],"dissertation":[83],"nonparametric":[86,102,143,154],"testing":[87],"hypotheses":[89],"about":[90],"ROC":[91,113,165],"curves":[92],"paired":[95],"design":[96],"setting.":[97],"Presently":[98],"only":[99],"few":[101],"are":[104],"available":[105],"task":[108],"comparing":[110,157],"two":[111],"correlated":[112],"curves.":[114],"Thus":[115],"we":[116,135,171,186,208],"focus":[117],"on":[118],"basic":[120],"problem":[121],"leaving":[122],"extensions":[124],"complex":[127],"settings":[128],"future":[130],"research.":[131],"In":[132],"work,":[134],"study":[136],"small-sample":[138],"conventional":[142],"method":[144],"presented":[145],"by":[146],"DeLong":[147],"et":[148],"al.":[149],"develop":[151,209],"three":[152],"novel":[153],"approaches":[155],"systems":[159],"using":[160],"area":[162],"under":[163],"curve.":[166],"permutation":[168],"approach":[169,214],"that":[170,215],"present":[172],"enables":[173],"conducting":[174],"exact":[176],"test":[177],"allows":[179],"easy-to-use":[182],"asymptotic":[183,193],"approximation.":[184],"Next,":[185],"derive":[187],"closed-form":[189],"bootstrap-variance,":[190],"construct":[191],"test,":[194],"compare":[196],"them":[197],"existing":[200],"competitors.":[201],"Finally":[202],"exploiting":[203],"idea":[205],"\"discordances\"":[207],"conceptually":[211],"new":[212],"conditional":[213],"offers":[216],"advantages":[217],"certain":[219],"types":[220],"studies.":[222]},"counts_by_year":[{"year":2012,"cited_by_count":1}],"updated_date":"2026-11-06T12:05:46.655746","created_date":"2016-06-24T00:00:00"}
