{"id":"https://openalex.org/W2403391702","doi":null,"title":"Propensity score matching for causal inference with relational data","display_name":"Propensity score matching for causal inference with relational data","publication_year":2014,"publication_date":"2014-07-27","ids":{"openalex":"https://openalex.org/W2403391702","mag":"2403391702"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.659.9568","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.659.9568","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ceur-ws.org/Vol-1274/uai2014ci_paper5.pdf","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5063845534","display_name":"David T. Arbour","orcid":"https://orcid.org/0000-0002-9932-7657","observed_orcids":["https://orcid.org/0000-0002-9932-7657"]},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Arbour","raw_affiliation_strings":["[School of Computer Science, University of Massachusetts Amherst, Amherst, MA]"],"raw_orcid":"https://orcid.org/0000-0002-9932-7657","affiliations":[{"raw_affiliation_string":"[School of Computer Science, University of Massachusetts Amherst, Amherst, MA]","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018278769","display_name":"Katerina Marazopoulou","orcid":"https://orcid.org/0000-0002-0509-4224","observed_orcids":["https://orcid.org/0000-0002-0509-4224"]},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Katerina Marazopoulou","raw_affiliation_strings":["[School of Computer Science, University of Massachusetts Amherst, Amherst, MA]"],"raw_orcid":"https://orcid.org/0000-0002-0509-4224","affiliations":[{"raw_affiliation_string":"[School of Computer Science, University of Massachusetts Amherst, Amherst, MA]","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086736896","display_name":"Dan Garant","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dan Garant","raw_affiliation_strings":["[School of Computer Science, University of Massachusetts Amherst, Amherst, MA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"[School of Computer Science, University of Massachusetts Amherst, Amherst, MA]","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006681132","display_name":"David D. Jensen","orcid":"https://orcid.org/0000-0001-5653-3349","observed_orcids":["https://orcid.org/0000-0001-5653-3349"]},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Jensen","raw_affiliation_strings":["[School of Computer Science, University of Massachusetts Amherst, Amherst, MA]"],"raw_orcid":"https://orcid.org/0000-0001-5653-3349","affiliations":[{"raw_affiliation_string":"[School of Computer Science, University of Massachusetts Amherst, Amherst, MA]","institution_ids":["https://openalex.org/I24603500"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24603500"],"apc_list":null,"apc_paid":null,"fwci":0.3292,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.60510806,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"25","last_page":"34"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9872999787330627,"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/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9872999787330627,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.003100000089034438,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.0003000000142492354,"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/propensity-score-matching","display_name":"propensity score matching","score":1.0},{"id":"https://openalex.org/keywords/causal-inference","display_name":"causal inference","score":0.9810000061988831},{"id":"https://openalex.org/keywords/relational-data","display_name":"relational data","score":0.9679999947547913},{"id":"https://openalex.org/keywords/confounding-variables","display_name":"confounding variables","score":0.7459999918937683},{"id":"https://openalex.org/keywords/relational-variables","display_name":"relational variables","score":0.8320000171661377},{"id":"https://openalex.org/keywords/entity-identifiers","display_name":"entity identifiers","score":0.9589999914169312},{"id":"https://openalex.org/keywords/latent-confounders","display_name":"latent confounders","score":0.9070000052452087},{"id":"https://openalex.org/keywords/observational-data","display_name":"observational data","score":0.7139999866485596}],"concepts":[{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.719436764717102},{"id":"https://openalex.org/C17923572","wikidata":"https://www.wikidata.org/wiki/Q7250160","display_name":"Propensity score matching","level":2,"score":0.7168464064598083},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.642291784286499},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.6067189574241638},{"id":"https://openalex.org/C77350462","wikidata":"https://www.wikidata.org/wiki/Q1125472","display_name":"Confounding","level":2,"score":0.5983580350875854},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5673109889030457},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5431094169616699},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5405648350715637},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4684370160102844},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.4668368101119995},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4217022955417633},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30418235063552856},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.2890564799308777},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2703893482685089},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23036250472068787},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.659.9568","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.659.9568","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ceur-ws.org/Vol-1274/uai2014ci_paper5.pdf","raw_type":"text"},{"id":"mag:2403391702","doi":null,"is_oa":false,"landing_page_url":"http://ceur-ws.org/Vol-1274/uai2014ci_paper5.pdf","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":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W28038548","https://openalex.org/W1515242458","https://openalex.org/W1585529040","https://openalex.org/W1602177480","https://openalex.org/W1606557745","https://openalex.org/W1860880244","https://openalex.org/W1969168383","https://openalex.org/W1986817546","https://openalex.org/W1995906082","https://openalex.org/W1999822211","https://openalex.org/W2002646960","https://openalex.org/W2012797835","https://openalex.org/W2018528171","https://openalex.org/W2028040032","https://openalex.org/W2029941278","https://openalex.org/W2055296410","https://openalex.org/W2122771444","https://openalex.org/W2122821666","https://openalex.org/W2132917208","https://openalex.org/W2139577967","https://openalex.org/W2140127353","https://openalex.org/W2146232090","https://openalex.org/W2150291618","https://openalex.org/W2155163959","https://openalex.org/W2164179075","https://openalex.org/W2215320577","https://openalex.org/W3122812581"],"related_works":["https://openalex.org/W2894814486","https://openalex.org/W4296363906","https://openalex.org/W2910632137","https://openalex.org/W2347664007","https://openalex.org/W6922479878","https://openalex.org/W4401388448","https://openalex.org/W7029092417","https://openalex.org/W6885088447","https://openalex.org/W4394647314","https://openalex.org/W2792083307"],"abstract_inverted_index":{"Propensity":[0],"score":[1],"matching":[2],"(PSM)":[3],"is":[4],"a":[5,71,109],"widely":[6],"used":[7],"method":[8,59,118],"for":[9,103,124],"performing":[10],"causal":[11,125],"inference":[12,126],"with":[13,127],"observational":[14],"data.":[15,51,129],"PSM":[16,123],"requires":[17],"fully":[18],"specifying":[19],"the":[20,30,46,50,67,96,120],"set":[21,36,72,110],"of":[22,25,32,49,73,83,98,111,122],"confounding":[23],"variables":[24,43,64,100],"treatment":[26],"and":[27,70,87],"outcome.":[28],"In":[29,52],"case":[31],"relational":[33,40,47,63,68,85,128],"data,":[34],"this":[35,53],"may":[37],"include":[38],"non-intuitive":[39],"variables,":[41],"i.e.,":[42],"derived":[44],"from":[45],"structure":[48,69],"work,":[54],"we":[55,114],"provide":[56,91],"an":[57],"automated":[58],"to":[60],"derive":[61],"these":[62,99],"based":[65],"on":[66],"naive":[74],"confounders.":[75,106],"This":[76],"automatic":[77],"construc-tion":[78],"includes":[79],"two":[80],"unusual":[81],"classes":[82],"variables:":[84],"degree":[86],"entity":[88],"identifiers.":[89],"We":[90],"experimental":[92],"evidence":[93],"that":[94,116],"demon-strates":[95],"utility":[97],"in":[101],"ac-counting":[102],"certain":[104],"latent":[105],"Fi-nally,":[107],"through":[108],"synthetic":[112],"experiments,":[113],"show":[115],"our":[117],"improves":[119],"per-formance":[121],"1":[130]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2016-06-24T00:00:00"}
