{"id":"https://openalex.org/W4416677129","doi":"https://doi.org/10.1109/dsaa65442.2025.11248034","title":"A New Framework for Causal Inference Without Missing Data Analysis: Bayes Optimal Treatment Effect Estimation","display_name":"A New Framework for Causal Inference Without Missing Data Analysis: Bayes Optimal Treatment Effect Estimation","publication_year":2025,"publication_date":"2025-10-09","ids":{"openalex":"https://openalex.org/W4416677129","doi":"https://doi.org/10.1109/dsaa65442.2025.11248034"},"language":null,"primary_location":{"id":"doi:10.1109/dsaa65442.2025.11248034","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsaa65442.2025.11248034","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 12th International Conference on Data Science and Advanced Analytics (DSAA)","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/A5120428740","display_name":"Kohei Horinouchi","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kohei Horinouchi","raw_affiliation_strings":["Waseda University,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University,Tokyo,Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113585840","display_name":"S. Onishi","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shimpei Onishi","raw_affiliation_strings":["Waseda University,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University,Tokyo,Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110471799","display_name":"Toshiyasu Matsushima","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Toshiyasu Matsushima","raw_affiliation_strings":["Waseda University,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University,Tokyo,Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30110103,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.8590999841690063,"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":0.8590999841690063,"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":0.037300001829862595,"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":0.026000000536441803,"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/missing-data","display_name":"Missing data","score":0.6958000063896179},{"id":"https://openalex.org/keywords/causal-inference","display_name":"Causal inference","score":0.652999997138977},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5127999782562256},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.46549999713897705},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.45320001244544983},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.4124000072479248},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.3977000117301941},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.39590001106262207},{"id":"https://openalex.org/keywords/bayes-estimator","display_name":"Bayes estimator","score":0.39169999957084656},{"id":"https://openalex.org/keywords/causal-model","display_name":"Causal model","score":0.3853999972343445}],"concepts":[{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.6958000063896179},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.652999997138977},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5127999782562256},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.46549999713897705},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.45320001244544983},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.447299987077713},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4250999987125397},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41850000619888306},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.4124000072479248},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.3977000117301941},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.39590001106262207},{"id":"https://openalex.org/C68022304","wikidata":"https://www.wikidata.org/wiki/Q842217","display_name":"Bayes estimator","level":3,"score":0.39169999957084656},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.3853999972343445},{"id":"https://openalex.org/C89106044","wikidata":"https://www.wikidata.org/wiki/Q45284","display_name":"Likelihood function","level":3,"score":0.38510000705718994},{"id":"https://openalex.org/C95167961","wikidata":"https://www.wikidata.org/wiki/Q4483495","display_name":"Fiducial inference","level":5,"score":0.38029998540878296},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3797999918460846},{"id":"https://openalex.org/C44492722","wikidata":"https://www.wikidata.org/wiki/Q327069","display_name":"Conditional probability","level":2,"score":0.3756999969482422},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3560999929904938},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3361999988555908},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.33410000801086426},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.3262999951839447},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.31119999289512634},{"id":"https://openalex.org/C89337504","wikidata":"https://www.wikidata.org/wiki/Q4828276","display_name":"Average treatment effect","level":3,"score":0.3070000112056732},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2971999943256378},{"id":"https://openalex.org/C162376815","wikidata":"https://www.wikidata.org/wiki/Q2158281","display_name":"Frequentist inference","level":4,"score":0.2939999997615814},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.2904999852180481},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.2838999927043915},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.2802000045776367},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.27379998564720154},{"id":"https://openalex.org/C28901747","wikidata":"https://www.wikidata.org/wiki/Q177571","display_name":"Decision theory","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C101112237","wikidata":"https://www.wikidata.org/wiki/Q4874481","display_name":"Bayesian statistics","level":4,"score":0.25619998574256897},{"id":"https://openalex.org/C142291917","wikidata":"https://www.wikidata.org/wiki/Q4165283","display_name":"Bayes factor","level":4,"score":0.25589999556541443},{"id":"https://openalex.org/C149569020","wikidata":"https://www.wikidata.org/wiki/Q25098598","display_name":"Bayesian average","level":5,"score":0.2515999972820282}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dsaa65442.2025.11248034","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsaa65442.2025.11248034","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 12th International Conference on Data Science and Advanced Analytics (DSAA)","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":19,"referenced_works":["https://openalex.org/W1982941892","https://openalex.org/W2022450888","https://openalex.org/W2061624754","https://openalex.org/W2064790857","https://openalex.org/W2064903582","https://openalex.org/W2132917208","https://openalex.org/W2137370054","https://openalex.org/W2624816748","https://openalex.org/W2902990530","https://openalex.org/W2963989473","https://openalex.org/W3004404638","https://openalex.org/W3124999902","https://openalex.org/W3150893739","https://openalex.org/W3213393193","https://openalex.org/W4237650824","https://openalex.org/W4248145776","https://openalex.org/W4361009279","https://openalex.org/W4393152612","https://openalex.org/W4402466351"],"related_works":[],"abstract_inverted_index":{"One":[0],"of":[1,24,41,95,147],"the":[2,9,22,39,93,101,107,126,131,145,148],"major":[3],"models":[4],"in":[5],"causal":[6,67],"inference":[7,68],"is":[8,19],"Rubin":[10],"Causal":[11],"Model.":[12],"In":[13,59,122],"this":[14,34,60,96],"model,":[15],"treatment":[16,83,103,136],"effect":[17,84,104,137],"estimation":[18,85,105,133,138],"considered":[20],"within":[21],"framework":[23,40,65],"missing":[25,42,74],"data":[26,43,75],"analysis.":[27],"However,":[28],"many":[29],"previous":[30],"studies":[31],"based":[32,51,110],"on":[33,52,73,111],"model":[35,81],"have":[36,47],"not":[37,71],"adopted":[38],"analysis":[44],"and":[45,86],"instead":[46],"moved":[48],"to":[49,91],"discussions":[50],"conditional":[53],"probability":[54],"distributions":[55],"for":[56,66,82,129],"outcome":[57],"variables.":[58],"study,":[61],"we":[62,98,124],"propose":[63],"a":[64,78,117],"that":[69],"does":[70],"rely":[72],"analysis,":[76],"using":[77],"generalized":[79],"probabilistic":[80],"statistical":[87],"decision":[88,113],"theory.":[89],"Furthermore,":[90],"verify":[92],"effectiveness":[94],"framework,":[97],"analytically":[99],"derive":[100],"optimal":[102,132],"under":[106],"Bayesian":[108,112],"criterion":[109],"theory":[114],"by":[115],"assuming":[116],"linear":[118],"basis":[119],"function":[120],"model.":[121],"addition,":[123],"compare":[125],"proposed":[127],"method":[128],"deriving":[130],"with":[134],"conventional":[135,149],"methods":[139],"through":[140],"simulations.":[141],"This":[142],"comparison":[143],"clarifies":[144],"properties":[146],"methods.":[150]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-25T00:00:00"}