{"id":"https://openalex.org/W4281838020","doi":"https://doi.org/10.48550/arxiv.2206.02962","title":"Confounder Analysis in Measuring Representation in Product Funnels","display_name":"Confounder Analysis in Measuring Representation in Product Funnels","publication_year":2022,"publication_date":"2022-06-07","ids":{"openalex":"https://openalex.org/W4281838020","doi":"https://doi.org/10.48550/arxiv.2206.02962"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2206.02962","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.02962","pdf_url":"https://arxiv.org/pdf/2206.02962","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2206.02962","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076841025","display_name":"Jilei Yang","orcid":"https://orcid.org/0000-0002-2711-3203"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Jilei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5025685034","display_name":"Wentao Su","orcid":"https://orcid.org/0000-0002-5233-1093"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Su, Wentao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9697999954223633,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9697999954223633,"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/causal-inference","display_name":"Causal inference","score":0.8237383365631104},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6324597597122192},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5905094146728516},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5724965929985046},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5396222472190857},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5221120119094849},{"id":"https://openalex.org/keywords/confounding","display_name":"Confounding","score":0.5186971426010132},{"id":"https://openalex.org/keywords/observational-study","display_name":"Observational study","score":0.5105043649673462},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4931632876396179},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.4704042077064514},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4530576765537262},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.4485694468021393},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4299304485321045},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3058592975139618},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2780308425426483},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22521835565567017},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20620790123939514},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.07230767607688904}],"concepts":[{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.8237383365631104},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6324597597122192},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5905094146728516},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5724965929985046},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5396222472190857},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5221120119094849},{"id":"https://openalex.org/C77350462","wikidata":"https://www.wikidata.org/wiki/Q1125472","display_name":"Confounding","level":2,"score":0.5186971426010132},{"id":"https://openalex.org/C23131810","wikidata":"https://www.wikidata.org/wiki/Q818574","display_name":"Observational study","level":2,"score":0.5105043649673462},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4931632876396179},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.4704042077064514},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4530576765537262},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4485694468021393},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4299304485321045},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3058592975139618},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2780308425426483},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22521835565567017},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20620790123939514},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.07230767607688904},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2206.02962","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.02962","pdf_url":"https://arxiv.org/pdf/2206.02962","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2206.02962","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2206.02962","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2206.02962","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.02962","pdf_url":"https://arxiv.org/pdf/2206.02962","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3023719900","https://openalex.org/W4287798354","https://openalex.org/W3035083705","https://openalex.org/W2030287811","https://openalex.org/W4386534229","https://openalex.org/W3002087755","https://openalex.org/W4386150491","https://openalex.org/W2806152055","https://openalex.org/W4301105698","https://openalex.org/W3037877651"],"abstract_inverted_index":{"This":[0],"paper":[1],"discusses":[2],"an":[3,36],"application":[4],"of":[5],"Shapley":[6,53],"values":[7,54],"in":[8,27],"the":[9,18],"causal":[10],"inference":[11],"field,":[12],"specifically":[13],"on":[14],"how":[15],"to":[16,46],"select":[17],"top":[19],"confounder":[20],"variables":[21],"for":[22,62],"coarsened":[23],"exact":[24],"matching":[25],"method":[26],"a":[28,33,43],"scalable":[29],"way.":[30],"We":[31],"use":[32,44],"dataset":[34],"from":[35],"observational":[37],"experiment":[38],"involving":[39],"LinkedIn":[40],"members":[41],"as":[42],"case":[45],"test":[47],"its":[48,63],"applicability,":[49],"and":[50,58],"show":[51],"that":[52],"are":[55],"highly":[56],"informational":[57],"can":[59],"be":[60],"leveraged":[61],"robust":[64],"importance-ranking":[65],"capability.":[66]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}