{"id":"https://openalex.org/W4413127886","doi":"https://doi.org/10.3390/sym17081304","title":"Model Averaging for Heterogeneous Treatment Effects via Proximity Matching","display_name":"Model Averaging for Heterogeneous Treatment Effects via Proximity Matching","publication_year":2025,"publication_date":"2025-08-12","ids":{"openalex":"https://openalex.org/W4413127886","doi":"https://doi.org/10.3390/sym17081304"},"language":"en","primary_location":{"id":"doi:10.3390/sym17081304","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17081304","pdf_url":"https://www.mdpi.com/2073-8994/17/8/1304/pdf?version=1755003350","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/17/8/1304/pdf?version=1755003350","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112553208","display_name":"Zhihao Zhao","orcid":"https://orcid.org/0009-0000-3871-1324"},"institutions":[{"id":"https://openalex.org/I90259746","display_name":"Capital University of Economics and Business","ror":"https://ror.org/01r5sf951","country_code":"CN","type":"education","lineage":["https://openalex.org/I90259746"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihao Zhao","raw_affiliation_strings":["School of Statistics, Capital University of Economics and Business, Beijing 100070, China"],"affiliations":[{"raw_affiliation_string":"School of Statistics, Capital University of Economics and Business, Beijing 100070, China","institution_ids":["https://openalex.org/I90259746"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101273528","display_name":"Lingya Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I90259746","display_name":"Capital University of Economics and Business","ror":"https://ror.org/01r5sf951","country_code":"CN","type":"education","lineage":["https://openalex.org/I90259746"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingya Zhao","raw_affiliation_strings":["School of Labor Economics, Capital University of Economics and Business, Beijing 100070, China"],"affiliations":[{"raw_affiliation_string":"School of Labor Economics, Capital University of Economics and Business, Beijing 100070, China","institution_ids":["https://openalex.org/I90259746"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100726586","display_name":"Ying Wang","orcid":"https://orcid.org/0000-0002-1324-1159"},"institutions":[{"id":"https://openalex.org/I198645480","display_name":"North China University of Water Resources and Electric Power","ror":"https://ror.org/03acrzv41","country_code":"CN","type":"education","lineage":["https://openalex.org/I198645480"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ying Wang","raw_affiliation_strings":["School of Mathematics and Statistics, North China University of Water Resources and Electric Power, Zhengzhou 450045, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, North China University of Water Resources and Electric Power, Zhengzhou 450045, China","institution_ids":["https://openalex.org/I198645480"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100726586"],"corresponding_institution_ids":["https://openalex.org/I198645480"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20324786,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"17","issue":"8","first_page":"1304","last_page":"1304"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","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/T10136","display_name":"Statistical Methods and Inference","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/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9983999729156494,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9711999893188477,"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/computer-science","display_name":"Computer science","score":0.4929961860179901},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4652214050292969},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2793978154659271},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20843937993049622}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4929961860179901},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4652214050292969},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2793978154659271},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20843937993049622}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3390/sym17081304","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17081304","pdf_url":"https://www.mdpi.com/2073-8994/17/8/1304/pdf?version=1755003350","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3390/sym17081304","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17081304","pdf_url":"https://www.mdpi.com/2073-8994/17/8/1304/pdf?version=1755003350","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1352100883","display_name":null,"funder_award_id":"252300420912","funder_id":"https://openalex.org/F4320323845","funder_display_name":"Natural Science Foundation of Henan Province"}],"funders":[{"id":"https://openalex.org/F4320323845","display_name":"Natural Science Foundation of Henan Province","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4413127886.pdf","grobid_xml":"https://content.openalex.org/works/W4413127886.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W28038548","https://openalex.org/W1800261609","https://openalex.org/W1989780425","https://openalex.org/W1991114736","https://openalex.org/W1994672023","https://openalex.org/W2002595054","https://openalex.org/W2003103177","https://openalex.org/W2006290997","https://openalex.org/W2010647378","https://openalex.org/W2021136548","https://openalex.org/W2035035907","https://openalex.org/W2035240057","https://openalex.org/W2052025831","https://openalex.org/W2057331441","https://openalex.org/W2058248640","https://openalex.org/W2064903582","https://openalex.org/W2067838071","https://openalex.org/W2094368311","https://openalex.org/W2104103536","https://openalex.org/W2122196572","https://openalex.org/W2125251038","https://openalex.org/W2126292488","https://openalex.org/W2131967549","https://openalex.org/W2140299661","https://openalex.org/W2150291618","https://openalex.org/W2151367131","https://openalex.org/W2208550830","https://openalex.org/W2257889789","https://openalex.org/W2290516599","https://openalex.org/W2305754340","https://openalex.org/W2313134401","https://openalex.org/W2314750237","https://openalex.org/W2899943493","https://openalex.org/W2936845999","https://openalex.org/W3105049881","https://openalex.org/W3120121358","https://openalex.org/W3121356359","https://openalex.org/W3122542817","https://openalex.org/W3159416870","https://openalex.org/W4239728164","https://openalex.org/W4382679660","https://openalex.org/W6647435156","https://openalex.org/W6679873413","https://openalex.org/W6682564331","https://openalex.org/W6692346243"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Accurate":[0],"estimation":[1,116,124],"of":[2,11,27,57],"heterogeneous":[3],"treatment":[4,19],"effects":[5],"(HTEs)":[6],"serves":[7],"as":[8],"a":[9,135],"cornerstone":[10],"personalized":[12],"decision-making,":[13],"especially":[14],"in":[15],"observational":[16],"studies":[17],"where":[18],"assignment":[20],"is":[21,131],"not":[22],"randomized.":[23],"However,":[24],"the":[25,55,83,90,118,139],"presence":[26],"confounding":[28],"and":[29,68,126],"complex":[30],"covariate":[31],"structures":[32],"poses":[33],"significant":[34],"challenges":[35],"to":[36,53,76,113],"reliable":[37],"inference.":[38,149],"In":[39],"this":[40],"study,":[41],"we":[42],"develop":[43],"an":[44,71],"innovative":[45],"model":[46,73,105],"averaging":[47,74],"framework,":[48],"which":[49],"leverages":[50],"proximity-based":[51],"matching":[52,67],"enhance":[54],"accuracy":[56],"HTE":[58,104,115],"estimation.":[59],"The":[60,129],"method":[61,120,130],"constructs":[62],"pseudo-outcomes":[63],"via":[64],"proximity":[65],"score":[66],"subsequently":[69],"applies":[70],"optimal":[72],"procedure":[75],"these":[77],"matched":[78],"samples.":[79],"We":[80],"demonstrate":[81],"that":[82],"proposed":[84,119],"estimator":[85],"achieves":[86,121],"asymptotic":[87],"optimality":[88],"when":[89],"standard":[91,114],"regularity":[92],"conditions":[93],"are":[94],"met.":[95],"Simulation":[96],"studies,":[97],"adapted":[98],"from":[99,138],"benchmark":[100],"settings":[101],"for":[102,146],"evaluating":[103],"averaging,":[106],"confirm":[107],"its":[108,143],"superior":[109],"finite-sample":[110],"performance.":[111],"Compared":[112],"approaches,":[117],"consistently":[122],"lower":[123],"errors":[125],"reduced":[127],"variability.":[128],"further":[132],"validated":[133],"on":[134],"clinical":[136],"dataset":[137],"CPCRA":[140],"trial,":[141],"demonstrating":[142],"practical":[144],"value":[145],"individualized":[147],"causal":[148]},"counts_by_year":[],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}
