{"id":"https://openalex.org/W3015437516","doi":"https://doi.org/10.1287/mnsc.2019.3424","title":"Near-Optimal A-B Testing","display_name":"Near-Optimal A-B Testing","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015437516","doi":"https://doi.org/10.1287/mnsc.2019.3424","mag":"3015437516"},"language":"en","primary_location":{"id":"doi:10.1287/mnsc.2019.3424","is_oa":false,"landing_page_url":"https://doi.org/10.1287/mnsc.2019.3424","pdf_url":null,"source":{"id":"https://openalex.org/S33323087","display_name":"Management Science","issn_l":"0025-1909","issn":["0025-1909","1526-5501"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315699","host_organization_name":"Institute for Operations Research and the Management Sciences","host_organization_lineage":["https://openalex.org/P4310315699"],"host_organization_lineage_names":["Institute for Operations Research and the Management Sciences"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Management Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hdl.handle.net/1721.1/134546","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110871669","display_name":"Nikhil Bhat","orcid":null},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Nikhil Bhat","raw_affiliation_strings":["Graduate School of Business, Columbia University, New York, New York 10028;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Business, Columbia University, New York, New York 10028;","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037762932","display_name":"Vivek F. Farias","orcid":"https://orcid.org/0000-0002-5856-9246"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vivek F. Farias","raw_affiliation_strings":["Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139;"],"raw_orcid":"https://orcid.org/0000-0002-5856-9246","affiliations":[{"raw_affiliation_string":"Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139;","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026049014","display_name":"Ciamac C. Moallemi","orcid":"https://orcid.org/0000-0002-4489-9260"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ciamac C. Moallemi","raw_affiliation_strings":["Graduate School of Business, Columbia University, New York, New York 10028;"],"raw_orcid":"https://orcid.org/0000-0002-4489-9260","affiliations":[{"raw_affiliation_string":"Graduate School of Business, Columbia University, New York, New York 10028;","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028467952","display_name":"Deeksha Sinha","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Deeksha Sinha","raw_affiliation_strings":["Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5110871669"],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":6.1782,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.97274796,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"66","issue":"10","first_page":"4477","last_page":"4495"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.9976000189781189,"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/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.9976000189781189,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9916999936103821,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9898999929428101,"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/selection","display_name":"Selection (genetic algorithm)","score":0.6097556352615356},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.5974487066268921},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5922064781188965},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.571134626865387},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5420511364936829},{"id":"https://openalex.org/keywords/moment","display_name":"Moment (physics)","score":0.5294126272201538},{"id":"https://openalex.org/keywords/sequential-analysis","display_name":"Sequential analysis","score":0.4947473406791687},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.4709917902946472},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.42126697301864624},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31538501381874084},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21603897213935852},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.10572025179862976},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.10475459694862366}],"concepts":[{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6097556352615356},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.5974487066268921},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5922064781188965},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.571134626865387},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5420511364936829},{"id":"https://openalex.org/C179254644","wikidata":"https://www.wikidata.org/wiki/Q13222844","display_name":"Moment (physics)","level":2,"score":0.5294126272201538},{"id":"https://openalex.org/C80478641","wikidata":"https://www.wikidata.org/wiki/Q195771","display_name":"Sequential analysis","level":2,"score":0.4947473406791687},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.4709917902946472},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.42126697301864624},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31538501381874084},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21603897213935852},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.10572025179862976},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.10475459694862366},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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":"doi:10.1287/mnsc.2019.3424","is_oa":false,"landing_page_url":"https://doi.org/10.1287/mnsc.2019.3424","pdf_url":null,"source":{"id":"https://openalex.org/S33323087","display_name":"Management Science","issn_l":"0025-1909","issn":["0025-1909","1526-5501"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315699","host_organization_name":"Institute for Operations Research and the Management Sciences","host_organization_lineage":["https://openalex.org/P4310315699"],"host_organization_lineage_names":["Institute for Operations Research and the Management Sciences"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Management Science","raw_type":"journal-article"},{"id":"pmh:oai:dspace.mit.edu:1721.1/134546","is_oa":true,"landing_page_url":"https://hdl.handle.net/1721.1/134546","pdf_url":null,"source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"MIT web domain","raw_type":"http://purl.org/eprint/type/JournalArticle"}],"best_oa_location":{"id":"pmh:oai:dspace.mit.edu:1721.1/134546","is_oa":true,"landing_page_url":"https://hdl.handle.net/1721.1/134546","pdf_url":null,"source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"MIT web domain","raw_type":"http://purl.org/eprint/type/JournalArticle"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W625185647","https://openalex.org/W1491087240","https://openalex.org/W1492655370","https://openalex.org/W1492677567","https://openalex.org/W1568307856","https://openalex.org/W1596538644","https://openalex.org/W1981888880","https://openalex.org/W1982591092","https://openalex.org/W1985123706","https://openalex.org/W1996711428","https://openalex.org/W1998026787","https://openalex.org/W2000366267","https://openalex.org/W2007316542","https://openalex.org/W2009100229","https://openalex.org/W2009188663","https://openalex.org/W2012547755","https://openalex.org/W2016130389","https://openalex.org/W2042355708","https://openalex.org/W2044872750","https://openalex.org/W2053821946","https://openalex.org/W2057564132","https://openalex.org/W2065398693","https://openalex.org/W2077747785","https://openalex.org/W2092197982","https://openalex.org/W2103550289","https://openalex.org/W2110674418","https://openalex.org/W2114306298","https://openalex.org/W2151337887","https://openalex.org/W2156195892","https://openalex.org/W2157464642","https://openalex.org/W2161038231","https://openalex.org/W2217862056","https://openalex.org/W2519411794","https://openalex.org/W2610857016","https://openalex.org/W2904958625","https://openalex.org/W2912380945","https://openalex.org/W2936061372","https://openalex.org/W2955208713","https://openalex.org/W2965497096","https://openalex.org/W2990138404","https://openalex.org/W3102707029","https://openalex.org/W3103634497","https://openalex.org/W3121632328","https://openalex.org/W3125327405","https://openalex.org/W4300031234"],"related_works":["https://openalex.org/W2606073172","https://openalex.org/W4297609745","https://openalex.org/W2125356288","https://openalex.org/W2128302072","https://openalex.org/W2970622411","https://openalex.org/W2782875959","https://openalex.org/W2883361795","https://openalex.org/W2416193394","https://openalex.org/W2085584073","https://openalex.org/W4297609580"],"abstract_inverted_index":{"We":[0,90],"consider":[1,32],"the":[2,8,11,33,48,54,68,93,113,132],"problem":[3,34,66],"of":[4,10,19,35,50,53,115,134,147],"A-B":[5],"testing":[6],"when":[7],"impact":[9],"treatment":[12,42,55],"is":[13,60],"marred":[14],"by":[15,98,174],"a":[16,44,61,145],"large":[17,111],"number":[18,114],"covariates.":[20],"Randomization":[21],"can":[22],"be":[23,76],"highly":[24],"inefficient":[25],"in":[26,67,95],"such":[27,130],"settings,":[28],"and":[29,74,105,140,160,179],"thus":[30],"we":[31,150],"optimally":[36],"allocating":[37],"test":[38],"subjects":[39,72],"to":[40,46,102],"either":[41],"with":[43,79,86],"view":[45],"maximizing":[47],"precision":[49,96],"our":[51,153],"estimate":[52],"effect.":[56],"Our":[57,118],"main":[58],"contribution":[59],"tractable":[62],"algorithm":[63],"for":[64],"this":[65,108],"online":[69],"setting,":[70],"where":[71],"arrive,":[73],"must":[75],"assigned,":[77],"sequentially,":[78],"covariates":[80,116],"drawn":[81],"from":[82],"an":[83],"elliptical":[84],"distribution":[85],"finite":[87],"second":[88],"moment.":[89],"further":[91],"characterize":[92],"gain":[94,109],"afforded":[97],"optimized":[99],"allocations":[100],"relative":[101],"randomized":[103],"allocations,":[104,139],"show":[106],"that":[107,125,152],"grows":[110],"as":[112,131],"grows.":[117],"dynamic":[119],"optimization":[120],"framework":[121],"admits":[122],"several":[123],"generalizations":[124],"incorporate":[126],"important":[127],"operational":[128],"constraints":[129],"consideration":[133],"selection":[135,162],"bias,":[136],"budgets":[137],"on":[138],"endogenous":[141],"stopping":[142],"times.":[143],"In":[144],"set":[146],"numerical":[148],"experiments,":[149],"demonstrate":[151],"method":[154],"simultaneously":[155],"offers":[156],"better":[157],"statistical":[158],"efficiency":[159],"less":[161],"bias":[163],"than":[164],"state-of-the-art":[165],"competing":[166],"biased":[167],"coin":[168],"designs.":[169],"This":[170],"paper":[171],"was":[172],"accepted":[173],"Noah":[175],"Gans,":[176],"stochastic":[177],"models":[178],"simulation.":[180]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}