{"id":"https://openalex.org/W4401863592","doi":"https://doi.org/10.1145/3637528.3671631","title":"False Positives in A/B Tests","display_name":"False Positives in A/B Tests","publication_year":2024,"publication_date":"2024-08-24","ids":{"openalex":"https://openalex.org/W4401863592","doi":"https://doi.org/10.1145/3637528.3671631"},"language":"en","primary_location":{"id":"doi:10.1145/3637528.3671631","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637528.3671631","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-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/A5037339239","display_name":"Ron Kohavi","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ron Kohavi","raw_affiliation_strings":["Kohavi, Los Altos, CA, USA"],"affiliations":[{"raw_affiliation_string":"Kohavi, Los Altos, CA, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089982054","display_name":"Nanyu Chen","orcid":"https://orcid.org/0000-0001-5150-1997"},"institutions":[{"id":"https://openalex.org/I4210106647","display_name":"Expedia Group (United States)","ror":"https://ror.org/01sh85g09","country_code":"US","type":"company","lineage":["https://openalex.org/I4210106647"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nanyu Chen","raw_affiliation_strings":["Expedia Group, San Francisco, CA, USA"],"affiliations":[{"raw_affiliation_string":"Expedia Group, San Francisco, CA, USA","institution_ids":["https://openalex.org/I4210106647"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5037339239"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.5357,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.93047257,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5240","last_page":"5250"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.9976999759674072,"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":0.9976999759674072,"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/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9812999963760376,"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":0.9653000235557556,"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/false-positive-paradox","display_name":"False positive paradox","score":0.8292003273963928},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6567956209182739},{"id":"https://openalex.org/keywords/true-positive-rate","display_name":"True positive rate","score":0.46314001083374023},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2535764276981354}],"concepts":[{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.8292003273963928},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6567956209182739},{"id":"https://openalex.org/C2989486834","wikidata":"https://www.wikidata.org/wiki/Q3808900","display_name":"True positive rate","level":2,"score":0.46314001083374023},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2535764276981354}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3637528.3671631","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637528.3671631","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W95299923","https://openalex.org/W1897139626","https://openalex.org/W1982716565","https://openalex.org/W2059707463","https://openalex.org/W2070815407","https://openalex.org/W2095720871","https://openalex.org/W2102945991","https://openalex.org/W2112508839","https://openalex.org/W2114688149","https://openalex.org/W2119303750","https://openalex.org/W2123817056","https://openalex.org/W2127151679","https://openalex.org/W2144981148","https://openalex.org/W2408017125","https://openalex.org/W2736848882","https://openalex.org/W2779567337","https://openalex.org/W2946387282","https://openalex.org/W2979658147","https://openalex.org/W3011423189","https://openalex.org/W3119325546","https://openalex.org/W3150893739","https://openalex.org/W4205719079","https://openalex.org/W4206205808","https://openalex.org/W4210743765","https://openalex.org/W4235859934","https://openalex.org/W4242589154","https://openalex.org/W4308588526","https://openalex.org/W4312332171","https://openalex.org/W4313448337","https://openalex.org/W4323528060","https://openalex.org/W6676237016","https://openalex.org/W6751060025"],"related_works":["https://openalex.org/W2027184711","https://openalex.org/W3129715955","https://openalex.org/W1557094818","https://openalex.org/W4287692494","https://openalex.org/W3047594718","https://openalex.org/W2953243682","https://openalex.org/W3027053746","https://openalex.org/W4299651861","https://openalex.org/W4386222044","https://openalex.org/W2099261052"],"abstract_inverted_index":{"A/B":[0,52],"tests,":[1,53],"or":[2,51],"online":[3],"controlled":[4],"experiments,":[5,50,170],"are":[6,86,123,152,231],"used":[7,234],"heavily":[8],"in":[9,25,33,56,74,154,195,227],"the":[10,19,22,30,34,37,40,61,78,84,130,165,172,221],"software":[11,49,156],"industry":[12,131],"to":[13,39,83,92,112,163,203,213],"evaluate":[14],"implementations":[15],"of":[16,42,119,135,141,169,220],"ideas,":[17],"as":[18],"paradigm":[20],"is":[21,60,99,107],"gold":[23],"standard":[24,132],"science":[26],"for":[27,102,192],"establishing":[28],"causality:":[29],"changes":[31,38],"introduced":[32],"treatment":[35],"caused":[36],"metrics":[41],"interest":[43],"with":[44,146,217],"high":[45,139],"probability.":[46],"What":[47],"distinguishes":[48],"from":[54,95,183],"experiments":[55,110,202,226],"many":[57,155],"other":[58],"domains":[59],"scale":[62],"(e.g.,":[63,88],"over":[64],"100":[65],"experiment":[66,98],"treatments":[67],"may":[68],"launch":[69],"on":[70],"a":[71,89,96,100,138,189,210,218],"given":[72,171],"workday":[73],"large":[75],"companies)":[76],"and":[77,116,180,185,225],"effect":[79],"sizes":[80],"that":[81,108,199,230],"matter":[82],"business":[85],"small":[87,211],"3%":[90],"improvement":[91],"conversion":[93],"rate":[94,168,175],"single":[97],"cause":[101],"celebration).":[103],"The":[104],"humbling":[105],"reality":[106],"most":[109,124],"fail":[111],"improve":[113],"key":[114],"metrics,":[115],"success":[117,128,167],"rates":[118],"only":[120],"about":[121,148],"10-20%":[122],"common.":[125],"With":[126],"low":[127],"rates,":[129],"alpha":[133],"threshold":[134],"0.05":[136],"implies":[137],"probability":[140],"false":[142,150,205],"positives.":[143],"We":[144,158,187,215],"begin":[145],"motivation":[147],"why":[149],"positives":[151],"expensive":[153],"domains.":[157],"then":[159],"offer":[160,188],"several":[161],"approaches":[162],"estimate":[164],"true":[166],"observed":[173],"\"win\"":[174],"(statistically":[176],"significant":[177],"positive":[178],"improvements),":[179],"show":[181],"examples":[182],"Expedia":[184],"Optimizely.":[186],"modified":[190],"procedure":[191],"experimentation,":[193],"based":[194],"sequential":[196],"group":[197],"testing,":[198],"selectively":[200],"extends":[201],"reduce":[204],"positives,":[206],"increase":[207,212],"power,":[208],"at":[209],"runtime.":[214],"conclude":[216],"discussion":[219],"difference":[222],"between":[223],"ideas":[224],"practice,":[228],"terms":[229],"often":[232],"incorrectly":[233],"interchangeably.":[235]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4}],"updated_date":"2026-04-01T17:29:45.350535","created_date":"2025-10-10T00:00:00"}
