{"id":"https://openalex.org/W2593975807","doi":"https://doi.org/10.1145/3027385.3029428","title":"Quasi-experimental design for causal inference using Python and Apache Spark","display_name":"Quasi-experimental design for causal inference using Python and Apache Spark","publication_year":2017,"publication_date":"2017-02-27","ids":{"openalex":"https://openalex.org/W2593975807","doi":"https://doi.org/10.1145/3027385.3029428","mag":"2593975807"},"language":"en","primary_location":{"id":"doi:10.1145/3027385.3029428","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3027385.3029428","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Seventh International Learning Analytics & Knowledge Conference","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/A5051765050","display_name":"Shirin Mojarad","orcid":null},"institutions":[{"id":"https://openalex.org/I4210126214","display_name":"McGraw-Hill Education (United States)","ror":"https://ror.org/034x1ve75","country_code":"US","type":"company","lineage":["https://openalex.org/I4210126214"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shirin Mojarad","raw_affiliation_strings":["McGraw-Hill Education"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"McGraw-Hill Education","institution_ids":["https://openalex.org/I4210126214"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057574366","display_name":"Nicholas Lewkow","orcid":null},"institutions":[{"id":"https://openalex.org/I4210126214","display_name":"McGraw-Hill Education (United States)","ror":"https://ror.org/034x1ve75","country_code":"US","type":"company","lineage":["https://openalex.org/I4210126214"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nicholas Lewkow","raw_affiliation_strings":["McGraw-Hill Education"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"McGraw-Hill Education","institution_ids":["https://openalex.org/I4210126214"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057179211","display_name":"Alfred Essa","orcid":null},"institutions":[{"id":"https://openalex.org/I4210126214","display_name":"McGraw-Hill Education (United States)","ror":"https://ror.org/034x1ve75","country_code":"US","type":"company","lineage":["https://openalex.org/I4210126214"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alfred Essa","raw_affiliation_strings":["McGraw-Hill Education"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"McGraw-Hill Education","institution_ids":["https://openalex.org/I4210126214"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100436760","display_name":"Jie Zhang","orcid":"https://orcid.org/0000-0002-5348-7671"},"institutions":[{"id":"https://openalex.org/I4210126214","display_name":"McGraw-Hill Education (United States)","ror":"https://ror.org/034x1ve75","country_code":"US","type":"company","lineage":["https://openalex.org/I4210126214"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jie Zhang","raw_affiliation_strings":["McGraw-Hill Education"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"McGraw-Hill Education","institution_ids":["https://openalex.org/I4210126214"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022063576","display_name":"Jacqueline Feild","orcid":null},"institutions":[{"id":"https://openalex.org/I4210126214","display_name":"McGraw-Hill Education (United States)","ror":"https://ror.org/034x1ve75","country_code":"US","type":"company","lineage":["https://openalex.org/I4210126214"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jacqueline Feild","raw_affiliation_strings":["McGraw-Hill Education"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"McGraw-Hill Education","institution_ids":["https://openalex.org/I4210126214"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210126214"],"apc_list":null,"apc_paid":null,"fwci":0.2396,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.567753,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"502","last_page":"503"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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/T10674","display_name":"School Choice and Performance","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/3304","display_name":"Education"},"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/T10467","display_name":"Psychometric Methodologies and Testing","score":0.9790999889373779,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/causal-inference","display_name":"Causal inference","score":0.8234592080116272},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6975511908531189},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.6945539712905884},{"id":"https://openalex.org/keywords/observational-study","display_name":"Observational study","score":0.5710960626602173},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5417578220367432},{"id":"https://openalex.org/keywords/causality","display_name":"Causality (physics)","score":0.5129306316375732},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.4921373724937439},{"id":"https://openalex.org/keywords/learning-analytics","display_name":"Learning analytics","score":0.4876900911331177},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.47707831859588623},{"id":"https://openalex.org/keywords/randomized-experiment","display_name":"Randomized experiment","score":0.42996177077293396},{"id":"https://openalex.org/keywords/curriculum","display_name":"Curriculum","score":0.42367154359817505},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40702909231185913},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37320077419281006},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.2271285057067871},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.16902393102645874},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.08866271376609802}],"concepts":[{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.8234592080116272},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6975511908531189},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.6945539712905884},{"id":"https://openalex.org/C23131810","wikidata":"https://www.wikidata.org/wiki/Q818574","display_name":"Observational study","level":2,"score":0.5710960626602173},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5417578220367432},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.5129306316375732},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.4921373724937439},{"id":"https://openalex.org/C2777648619","wikidata":"https://www.wikidata.org/wiki/Q2845208","display_name":"Learning analytics","level":2,"score":0.4876900911331177},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.47707831859588623},{"id":"https://openalex.org/C155108698","wikidata":"https://www.wikidata.org/wiki/Q1231081","display_name":"Randomized experiment","level":2,"score":0.42996177077293396},{"id":"https://openalex.org/C47177190","wikidata":"https://www.wikidata.org/wiki/Q207137","display_name":"Curriculum","level":2,"score":0.42367154359817505},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40702909231185913},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37320077419281006},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2271285057067871},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.16902393102645874},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.08866271376609802},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3027385.3029428","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3027385.3029428","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Seventh International Learning Analytics & Knowledge Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6899999976158142}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W149611134","https://openalex.org/W1581376112","https://openalex.org/W1966974590","https://openalex.org/W1982910299","https://openalex.org/W2013350088","https://openalex.org/W2036193982","https://openalex.org/W2139865581","https://openalex.org/W2150291618","https://openalex.org/W2152849583","https://openalex.org/W2155163959","https://openalex.org/W2164638355"],"related_works":["https://openalex.org/W4389471064","https://openalex.org/W2119346805","https://openalex.org/W2574301230","https://openalex.org/W1547624382","https://openalex.org/W4322726883","https://openalex.org/W4320159092","https://openalex.org/W3005312434","https://openalex.org/W4313559754","https://openalex.org/W1730782591","https://openalex.org/W4388998033"],"abstract_inverted_index":{"Educational":[0],"practitioners":[1],"and":[2,22,76,132,165,176],"policy":[3],"makers":[4],"require":[5],"evidence":[6],"supporting":[7],"claims":[8],"about":[9],"educational":[10,88,136,149,184],"efficacy.":[11],"Evidence":[12],"is":[13,50,122,155],"often":[14],"found":[15],"using":[16,118],"causal":[17,109,143,188],"relationships":[18],"between":[19],"education":[20,35,112],"inputs":[21,113],"student":[23,54,115],"learning":[24,55,116],"outcomes.":[25,56],"Causal":[26],"inference":[27,144],"covers":[28],"a":[29,43,63,171,180,191],"wide":[30],"range":[31],"of":[32,111,148,159],"topics":[33],"in":[34,52,86,135,145],"research,":[36],"including":[37],"efficacy":[38],"studies":[39,72],"to":[40,67,84,128,186,196],"prove":[41],"if":[42],"new":[44],"policy,":[45],"software,":[46],"curriculum":[47],"or":[48],"intervention":[49],"effective":[51],"improving":[53],"Randomized":[57],"controlled":[58],"trials":[59],"(RCT)":[60],"are":[61,73,194],"considered":[62],"gold":[64],"standard":[65],"method":[66],"demonstrate":[68],"causality.":[69],"However,":[70],"these":[71],"expensive,":[74],"timely":[75],"costly,":[77],"as":[78,80,179],"well":[79],"not":[81],"being":[82],"ethical":[83],"conduct":[85,187],"many":[87,129],"contexts.":[89],"Causality":[90],"can":[91],"also":[92],"be":[93],"deducted":[94],"purely":[95],"from":[96],"observational":[97,119],"data.":[98,120,153],"In":[99,138],"this":[100,139],"tutorial,":[101,140],"we":[102,141],"will":[103],"review":[104],"methodologies":[105],"for":[106,183],"estimating":[107],"the":[108,146,156],"effects":[110],"on":[114],"outcomes":[117],"This":[121,154],"an":[123],"inherently":[124],"complex":[125],"task":[126],"due":[127],"hidden":[130],"variables":[131],"their":[133],"interrelationships":[134],"research.":[137],"discuss":[142],"context":[147],"research":[150],"with":[151,174,199],"big":[152],"first":[157],"tutorial":[158],"its":[160],"kind":[161],"at":[162],"Learning":[163],"Analytics":[164],"Knowledge":[166],"Conference":[167],"(LAK)":[168],"that":[169],"provides":[170],"hands-on":[172],"experience":[173],"Python":[175],"Apache":[177],"Spark":[178],"practical":[181],"tool":[182],"researchers":[185],"inference.":[189],"As":[190],"prerequisite,":[192],"attendees":[193],"required":[195],"have":[197],"familiarity":[198],"Python.":[200]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}