{"id":"https://openalex.org/W2949574684","doi":"https://doi.org/10.1145/3292500.3330769","title":"The Identification and Estimation of Direct and Indirect Effects in A/B Tests through Causal Mediation Analysis","display_name":"The Identification and Estimation of Direct and Indirect Effects in A/B Tests through Causal Mediation Analysis","publication_year":2019,"publication_date":"2019-07-25","ids":{"openalex":"https://openalex.org/W2949574684","doi":"https://doi.org/10.1145/3292500.3330769","mag":"2949574684"},"language":"en","primary_location":{"id":"doi:10.1145/3292500.3330769","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3292500.3330769","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1906.09757","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Xuan Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210112773","display_name":"Etsy (United States)","ror":"https://ror.org/01kzp9g64","country_code":"US","type":"company","lineage":["https://openalex.org/I4210112773"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xuan Yin","raw_affiliation_strings":["Etsy, Inc., Brooklyn, NY, USA"],"affiliations":[{"raw_affiliation_string":"Etsy, Inc., Brooklyn, NY, USA","institution_ids":["https://openalex.org/I4210112773"]}]},{"author_position":"last","author":{"id":null,"display_name":"Liangjie Hong","orcid":null},"institutions":[{"id":"https://openalex.org/I4210112773","display_name":"Etsy (United States)","ror":"https://ror.org/01kzp9g64","country_code":"US","type":"company","lineage":["https://openalex.org/I4210112773"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liangjie Hong","raw_affiliation_strings":["Etsy, Inc., Brooklyn, NY, USA"],"affiliations":[{"raw_affiliation_string":"Etsy, Inc., Brooklyn, NY, USA","institution_ids":["https://openalex.org/I4210112773"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210112773"],"apc_list":null,"apc_paid":null,"fwci":1.6841,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.85750043,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2989","last_page":"2999"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9980999827384949,"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":0.9980999827384949,"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/T13051","display_name":"Qualitative Comparative Analysis Research","score":0.9710000157356262,"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"}},{"id":"https://openalex.org/T12892","display_name":"Social Power and Status Dynamics","score":0.9035000205039978,"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/identification","display_name":"Identification (biology)","score":0.6784999966621399},{"id":"https://openalex.org/keywords/mediation","display_name":"Mediation","score":0.5830000042915344},{"id":"https://openalex.org/keywords/causal-model","display_name":"Causal model","score":0.5149999856948853},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.47519999742507935},{"id":"https://openalex.org/keywords/causal-analysis","display_name":"Causal analysis","score":0.435699999332428},{"id":"https://openalex.org/keywords/causal-inference","display_name":"Causal inference","score":0.420199990272522}],"concepts":[{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6784999966621399},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5964000225067139},{"id":"https://openalex.org/C179420905","wikidata":"https://www.wikidata.org/wiki/Q223871","display_name":"Mediation","level":2,"score":0.5830000042915344},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.5149999856948853},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.47600001096725464},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.47519999742507935},{"id":"https://openalex.org/C2987525970","wikidata":"https://www.wikidata.org/wiki/Q96374569","display_name":"Causal analysis","level":2,"score":0.435699999332428},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.420199990272522},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.4092999994754791},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.388700008392334},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.36399999260902405},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.3183000087738037},{"id":"https://openalex.org/C2986587452","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical analysis","level":2,"score":0.3165999948978424},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3075000047683716},{"id":"https://openalex.org/C79897977","wikidata":"https://www.wikidata.org/wiki/Q5054568","display_name":"Causal chain","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2847999930381775},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2822999954223633},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2689000070095062},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2632000148296356},{"id":"https://openalex.org/C2777093003","wikidata":"https://www.wikidata.org/wiki/Q6508345","display_name":"Lead (geology)","level":2,"score":0.2581999897956848}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3292500.3330769","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3292500.3330769","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1906.09757","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1906.09757","pdf_url":"https://arxiv.org/pdf/1906.09757","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":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1906.09757","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1906.09757","pdf_url":"https://arxiv.org/pdf/1906.09757","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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W247640289","https://openalex.org/W1612884388","https://openalex.org/W1767520447","https://openalex.org/W1978108654","https://openalex.org/W2053879494","https://openalex.org/W2056621649","https://openalex.org/W2109416443","https://openalex.org/W2142995921","https://openalex.org/W2152431454","https://openalex.org/W2155203925","https://openalex.org/W2160326831","https://openalex.org/W2321885410","https://openalex.org/W2575871980","https://openalex.org/W2575883117","https://openalex.org/W3121505931","https://openalex.org/W4292811746"],"related_works":[],"abstract_inverted_index":{"E-commerce":[0,65],"companies":[1],"have":[2],"a":[3,27,35,85,121,152],"number":[4],"of":[5,23,37,56,68,164,174],"online":[6],"products,":[7],"such":[8],"as":[9,120],"organic":[10],"search,":[11,13],"sponsored":[12],"and":[14,48,53,70,161,185],"recommendation":[15],"modules,":[16],"to":[17,32,78,93,103,125,155],"fulfill":[18],"customer":[19],"needs.":[20],"Although":[21],"each":[22],"these":[24,107],"products":[25,73,108],"provides":[26,133],"unique":[28],"opportunity":[29],"for":[30,46,50],"users":[31,47,92],"interact":[33],"with":[34],"portion":[36],"the":[38,82,104,127,165,168,172,175],"overall":[39,61],"inventory,":[40],"they":[41],"are":[42,109,145],"all":[43],"similar":[44],"channels":[45],"compete":[49],"limited":[51],"time":[52],"monetary":[54],"budgets":[55],"users.":[57],"To":[58],"optimize":[59],"users'":[60],"experiences":[62],"on":[63,136,188],"an":[64],"platform,":[66],"instead":[67],"understanding":[69],"improving":[71],"different":[72,192],"separately,":[74],"it":[75],"is":[76],"important":[77],"gain":[79],"insights":[80],"into":[81],"evidence":[83],"that":[84,106],"change":[86,94],"in":[87,97,147,157,178],"one":[88],"product":[89],"would":[90],"induce":[91],"their":[95],"behaviors":[96],"others,":[98],"which":[99,144],"may":[100],"be":[101],"due":[102],"fact":[105],"functionally":[110],"similar.":[111],"In":[112,167],"this":[113],"paper,":[114],"we":[115,170],"introduce":[116],"causal":[117,129],"mediation":[118],"analysis":[119],"formal":[122],"statistical":[123],"tool":[124],"reveal":[126],"underlying":[128],"mechanisms.":[130],"Existing":[131],"literature":[132],"little":[134],"guidance":[135],"cases":[137],"where":[138],"multiple":[139],"unmeasured":[140],"causally-dependent":[141],"mediators":[142],"exist,":[143],"common":[146],"A/B":[148,183],"tests.":[149],"We":[150],"seek":[151],"novel":[153],"approach":[154],"identify":[156],"those":[158],"scenarios":[159],"direct":[160],"indirect":[162],"effects":[163],"treatment.":[166],"end,":[169],"demonstrate":[171],"effectiveness":[173],"proposed":[176],"method":[177],"data":[179],"from":[180],"Etsy's":[181],"real":[182],"tests":[184],"shed":[186],"lights":[187],"complex":[189],"relationships":[190],"between":[191],"products.":[193]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2019-06-27T00:00:00"}
