{"id":"https://openalex.org/W7162525299","doi":"https://doi.org/10.48550/arxiv.2605.26288","title":"Beyond Differences: Doubly Robust Meta-Learners for Ratio-Based Treatment Effects","display_name":"Beyond Differences: Doubly Robust Meta-Learners for Ratio-Based Treatment Effects","publication_year":2026,"publication_date":"2026-05-25","ids":{"openalex":"https://openalex.org/W7162525299","doi":"https://doi.org/10.48550/arxiv.2605.26288"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.26288","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.26288","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.26288","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137112042","display_name":"Michael Fuchs","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fuchs, Michael","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5056447828","display_name":"Dominik Krei\u00df","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kreiss, Dominik","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9830999970436096,"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":0.9830999970436096,"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/T10136","display_name":"Statistical Methods and Inference","score":0.001500000013038516,"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/T10206","display_name":"Meta-analysis and systematic reviews","score":0.0013000000035390258,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"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/observational-study","display_name":"Observational study","score":0.7932000160217285},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7175999879837036},{"id":"https://openalex.org/keywords/propensity-score-matching","display_name":"Propensity score matching","score":0.6962000131607056},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6582000255584717},{"id":"https://openalex.org/keywords/confounding","display_name":"Confounding","score":0.5796999931335449},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5006999969482422},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.483599990606308},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.39079999923706055},{"id":"https://openalex.org/keywords/robust-regression","display_name":"Robust regression","score":0.361299991607666}],"concepts":[{"id":"https://openalex.org/C23131810","wikidata":"https://www.wikidata.org/wiki/Q818574","display_name":"Observational study","level":2,"score":0.7932000160217285},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7175999879837036},{"id":"https://openalex.org/C17923572","wikidata":"https://www.wikidata.org/wiki/Q7250160","display_name":"Propensity score matching","level":2,"score":0.6962000131607056},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6582000255584717},{"id":"https://openalex.org/C77350462","wikidata":"https://www.wikidata.org/wiki/Q1125472","display_name":"Confounding","level":2,"score":0.5796999931335449},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5527999997138977},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5059999823570251},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5006999969482422},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.483599990606308},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.45089998841285706},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.430400013923645},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.39079999923706055},{"id":"https://openalex.org/C70259352","wikidata":"https://www.wikidata.org/wiki/Q1847839","display_name":"Robust regression","level":3,"score":0.361299991607666},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.3490000069141388},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.3416999876499176},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.34040001034736633},{"id":"https://openalex.org/C66912227","wikidata":"https://www.wikidata.org/wiki/Q2138712","display_name":"Regression discontinuity design","level":2,"score":0.3391000032424927},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.33399999141693115},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.33340001106262207},{"id":"https://openalex.org/C142259097","wikidata":"https://www.wikidata.org/wiki/Q5891314","display_name":"Homogeneity (statistics)","level":2,"score":0.3100999891757965},{"id":"https://openalex.org/C143095724","wikidata":"https://www.wikidata.org/wiki/Q515895","display_name":"Odds","level":3,"score":0.3059999942779541},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29820001125335693},{"id":"https://openalex.org/C2779190172","wikidata":"https://www.wikidata.org/wiki/Q4913888","display_name":"Binary data","level":3,"score":0.289000004529953},{"id":"https://openalex.org/C6571938","wikidata":"https://www.wikidata.org/wiki/Q3274486","display_name":"Omitted-variable bias","level":2,"score":0.28780001401901245},{"id":"https://openalex.org/C162144332","wikidata":"https://www.wikidata.org/wiki/Q1665305","display_name":"Instrumental variable","level":2,"score":0.28139999508857727},{"id":"https://openalex.org/C168563851","wikidata":"https://www.wikidata.org/wiki/Q1436668","display_name":"Randomized controlled trial","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2660999894142151},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2574999928474426},{"id":"https://openalex.org/C67226441","wikidata":"https://www.wikidata.org/wiki/Q1665389","display_name":"Robust statistics","level":3,"score":0.25029999017715454},{"id":"https://openalex.org/C155108698","wikidata":"https://www.wikidata.org/wiki/Q1231081","display_name":"Randomized experiment","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.26288","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.26288","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.26288","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.26288","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"When":[0],"treatment":[1],"effects":[2],"are":[3],"naturally":[4],"expressed":[5],"as":[6,9],"ratios":[7],"--":[8,15],"in":[10,105],"medicine,":[11],"pricing,":[12],"and":[13,81,85,129],"marketing":[14],"the":[16,25,49,97,100,113,135],"ratio-based":[17],"CATE":[18],"$\u03c4(x)":[19],"=":[20],"E[Y|W=1,X=x]":[21],"/":[22],"E[Y|W=0,X=x]$":[23],"is":[24,99],"appropriate":[26],"estimand.":[27],"Yet":[28],"existing":[29],"estimators":[30],"either":[31],"impose":[32],"a":[33,55],"log-linear":[34],"parametric":[35],"structure":[36],"or":[37],"apply":[38],"generic":[39],"regression":[40,115],"without":[41],"robustness":[42,89],"guarantees":[43],"for":[44,64,78,150],"this":[45],"functional.":[46],"We":[47,72],"introduce":[48],"Q-Learner,":[50],"which":[51],"decomposes":[52],"$\u03c4(x)$":[53],"into":[54],"product":[56],"of":[57],"two":[58,68],"odds":[59],"ratios,":[60],"reducing":[61],"ratio-CATE":[62],"estimation":[63],"binary":[65],"outcomes":[66],"to":[67],"propensity":[69,125],"classification":[70],"tasks.":[71],"further":[73],"derive":[74],"doubly":[75],"robust":[76],"augmentations":[77],"both":[79],"S/T-":[80],"Q-style":[82],"ratio":[83],"learners":[84,137],"characterize":[86],"their":[87],"distinct":[88],"properties.":[90],"In":[91],"benchmarks":[92],"on":[93,143],"seven":[94],"RCT":[95],"datasets,":[96,123],"Q-Learner":[98],"most":[101],"consistently":[102],"competitive":[103],"method":[104],"low-conversion":[106],"regimes,":[107],"where":[108,124],"its":[109],"propensity-only":[110],"construction":[111],"sidesteps":[112],"imbalanced":[114],"that":[116],"hurts":[117],"outcome-based":[118],"estimators.":[119],"On":[120],"four":[121],"observational":[122,152],"must":[126],"be":[127,132],"estimated":[128],"confounding":[130],"cannot":[131],"ruled":[133],"out,":[134],"DR":[136],"introduced":[138],"here":[139],"decisively":[140],"come":[141],"out":[142],"top,":[144],"making":[145],"them":[146],"practitioners'":[147],"natural":[148],"default":[149],"confounded":[151],"data.":[153]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-28T00:00:00"}
