{"id":"https://openalex.org/W2001010216","doi":"https://doi.org/10.1080/03610910903168595","title":"Transformed Logit Confidence Intervals for Small Populations in Single Capture\u2013Recapture Estimation","display_name":"Transformed Logit Confidence Intervals for Small Populations in Single Capture\u2013Recapture Estimation","publication_year":2009,"publication_date":"2009-09-04","ids":{"openalex":"https://openalex.org/W2001010216","doi":"https://doi.org/10.1080/03610910903168595","mag":"2001010216"},"language":"en","primary_location":{"id":"doi:10.1080/03610910903168595","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610910903168595","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"},"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/A5038833573","display_name":"Mauricio Sadinle","orcid":"https://orcid.org/0000-0002-7092-3877"},"institutions":[{"id":"https://openalex.org/I36243813","display_name":"Universidad Nacional de Colombia","ror":"https://ror.org/059yx9a68","country_code":"CO","type":"education","lineage":["https://openalex.org/I36243813"]}],"countries":["CO"],"is_corresponding":true,"raw_author_name":"Mauricio Sadinle","raw_affiliation_strings":["\n                   \n               Departamento de Estad\u00edstica, Universidad Nacional de Colombia, Bogot\u00e1, Colombia;\n                   \n               Conflict Analysis Resource Center \u2013 CERAC, Bogot\u00e1, Colombia","Conflict Analysis Resource Center \u2013 CERAC, Bogot\u00e1, Colombia","Departamento de Estad\u00edstica, Universidad Nacional de Colombia, Bogot\u00e1, Colombia"],"affiliations":[{"raw_affiliation_string":"\n                   \n               Departamento de Estad\u00edstica, Universidad Nacional de Colombia, Bogot\u00e1, Colombia;\n                   \n               Conflict Analysis Resource Center \u2013 CERAC, Bogot\u00e1, Colombia","institution_ids":["https://openalex.org/I36243813"]},{"raw_affiliation_string":"Conflict Analysis Resource Center \u2013 CERAC, Bogot\u00e1, Colombia","institution_ids":[]},{"raw_affiliation_string":"Departamento de Estad\u00edstica, Universidad Nacional de Colombia, Bogot\u00e1, Colombia","institution_ids":["https://openalex.org/I36243813"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5038833573"],"corresponding_institution_ids":["https://openalex.org/I36243813"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.10054988,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"38","issue":"9","first_page":"1909","last_page":"1924"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13546","display_name":"Census and Population Estimation","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9911999702453613,"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":0.9832000136375427,"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/confidence-interval","display_name":"Confidence interval","score":0.7854710817337036},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.7443942427635193},{"id":"https://openalex.org/keywords/logit","display_name":"Logit","score":0.7338012456893921},{"id":"https://openalex.org/keywords/odds","display_name":"Odds","score":0.5582107901573181},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.5421373248100281},{"id":"https://openalex.org/keywords/odds-ratio","display_name":"Odds ratio","score":0.5034584403038025},{"id":"https://openalex.org/keywords/mixed-logit","display_name":"Mixed logit","score":0.4565311670303345},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.44443267583847046},{"id":"https://openalex.org/keywords/coverage-probability","display_name":"Coverage probability","score":0.4391743838787079},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4298953711986542},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.42606109380722046},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.4258453845977783},{"id":"https://openalex.org/keywords/mark-and-recapture","display_name":"Mark and recapture","score":0.425680547952652},{"id":"https://openalex.org/keywords/demography","display_name":"Demography","score":0.2191510796546936},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1894875466823578}],"concepts":[{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.7854710817337036},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.7443942427635193},{"id":"https://openalex.org/C140331021","wikidata":"https://www.wikidata.org/wiki/Q1868104","display_name":"Logit","level":2,"score":0.7338012456893921},{"id":"https://openalex.org/C143095724","wikidata":"https://www.wikidata.org/wiki/Q515895","display_name":"Odds","level":3,"score":0.5582107901573181},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.5421373248100281},{"id":"https://openalex.org/C156957248","wikidata":"https://www.wikidata.org/wiki/Q1862216","display_name":"Odds ratio","level":2,"score":0.5034584403038025},{"id":"https://openalex.org/C95057490","wikidata":"https://www.wikidata.org/wiki/Q6883984","display_name":"Mixed logit","level":3,"score":0.4565311670303345},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.44443267583847046},{"id":"https://openalex.org/C2776292839","wikidata":"https://www.wikidata.org/wiki/Q5179217","display_name":"Coverage probability","level":3,"score":0.4391743838787079},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4298953711986542},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.42606109380722046},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4258453845977783},{"id":"https://openalex.org/C36528806","wikidata":"https://www.wikidata.org/wiki/Q796147","display_name":"Mark and recapture","level":3,"score":0.425680547952652},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.2191510796546936},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1894875466823578},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610910903168595","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610910903168595","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6600000262260437,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W44278768","https://openalex.org/W619032326","https://openalex.org/W966667953","https://openalex.org/W1510853657","https://openalex.org/W1564214970","https://openalex.org/W1633238894","https://openalex.org/W1894850789","https://openalex.org/W1970822599","https://openalex.org/W1986301390","https://openalex.org/W1989360245","https://openalex.org/W1997235487","https://openalex.org/W2007044505","https://openalex.org/W2038003834","https://openalex.org/W2044122171","https://openalex.org/W2046935327","https://openalex.org/W2060081924","https://openalex.org/W2065424415","https://openalex.org/W2065543268","https://openalex.org/W2068443247","https://openalex.org/W2074673068","https://openalex.org/W2076983043","https://openalex.org/W2094728279","https://openalex.org/W2117897510","https://openalex.org/W2141823261","https://openalex.org/W2160148537","https://openalex.org/W2228825211","https://openalex.org/W2232104586","https://openalex.org/W2313174853","https://openalex.org/W2316236334","https://openalex.org/W2319777021","https://openalex.org/W2322479613","https://openalex.org/W2327380363","https://openalex.org/W2328123077","https://openalex.org/W2333624796","https://openalex.org/W2488520097","https://openalex.org/W4230737632","https://openalex.org/W4232499084","https://openalex.org/W4293258535","https://openalex.org/W4399583916"],"related_works":["https://openalex.org/W1484225063","https://openalex.org/W1493625323","https://openalex.org/W1594919415","https://openalex.org/W2388811235","https://openalex.org/W3122575588","https://openalex.org/W1984791470","https://openalex.org/W2998360796","https://openalex.org/W2169860457","https://openalex.org/W4367291058","https://openalex.org/W1594899618"],"abstract_inverted_index":{"Abstract":[0],"The":[1,178],"good":[2,147],"performance":[3],"of":[4,41,44,46,52,69,158,202],"logit":[5,54,83,137],"confidence":[6,55,125],"intervals":[7,56,126],"for":[8,57,104,109,121,197,223],"the":[9,22,33,42,47,53,58,67,81,100,122,134,159,199,228],"odds":[10,24,34,59],"ratio":[11,25,35,60],"with":[12],"small":[13,105],"samples":[14],"is":[15,19,26,36,61,78,118,139,150],"well":[16],"known.":[17],"This":[18],"true":[20],"unless":[21],"actual":[23,95],"very":[27,140],"large.":[28],"In":[29],"single":[30,74,160],"capture\u2013recapture":[31,75,124,161],"estimation":[32],"equal":[37],"to":[38,65,88,99,113,142,152,181,212],"1":[39],"because":[40],"assumption":[43],"independence":[45],"samples.":[48],"Consequently,":[49],"a":[50,70,146],"transformation":[51],"proposed":[62,127],"in":[63,128,232],"order":[64],"estimate":[66],"size":[68],"closed":[71],"population":[72],"under":[73],"estimation.":[76],"It":[77],"found":[79],"that":[80,133],"transformed":[82,136],"interval,":[84],"after":[85],"adding":[86],".5":[87,135],"each":[89],"observed":[90],"count":[91],"before":[92],"computation,":[93],"has":[94,145],"coverage":[96],"probabilities":[97,111],"near":[98,112],"nominal":[101],"level":[102],"even":[103,108],"populations":[106],"and":[107,144,193,205,209,220,230],"capture":[110],"0":[114],"or":[115],"1,":[116],"which":[117],"not":[119],"guaranteed":[120],"other":[123],"statistical":[129],"literature.":[130],"Thus,":[131],"given":[132],"interval":[138],"simple":[141],"compute":[143],"performance,":[148],"it":[149],"appropriate":[151],"be":[153],"implemented":[154],"by":[155],"most":[156],"users":[157],"method.":[162],"Keywords:":[163],"Asymptotic":[164],"normalityCoverage":[165],"probabilityDual-system":[166],"estimationExpected":[167],"widthMonte":[168],"Carlo":[169],"studyOdds":[170],"ratioPivotal":[171],"statisticProfile":[172],"likelihoodMathematics":[173],"Subject":[174],"Classification:":[175],"62F2562P12":[176],"Acknowledgments":[177],"author":[179],"thanks":[180],"B.":[182],"P.":[183],"Urdinola,":[184],"L.":[185],"M.":[186],"Gonz\u00e1lez,":[187],"S.":[188,218],"T.":[189],"Buckland,":[190],"A.":[191,216],"Agresti,":[192],"an":[194],"anonymous":[195],"reviewer":[196],"reading":[198],"preliminary":[200],"versions":[201],"this":[203,233],"work":[204],"their":[206,224],"helpful":[207],"comments":[208],"suggestions.":[210],"Also,":[211],"C.":[213],"E.":[214],"Pardo,":[215],"Irlande,":[217],"Baillargeon,":[219],"L.-P.":[221],"Rivest":[222],"help":[225],"about":[226],"programing":[227],"simulations":[229],"computations":[231],"work.":[234]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}
