{"id":"https://openalex.org/W4416765798","doi":"https://doi.org/10.3390/info16121034","title":"Exchangeability and Bayesian Inference: A Theoretical and Computational Framework for Reliable Experimental Data Analysis","display_name":"Exchangeability and Bayesian Inference: A Theoretical and Computational Framework for Reliable Experimental Data Analysis","publication_year":2025,"publication_date":"2025-11-27","ids":{"openalex":"https://openalex.org/W4416765798","doi":"https://doi.org/10.3390/info16121034"},"language":"en","primary_location":{"id":"doi:10.3390/info16121034","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16121034","pdf_url":"https://www.mdpi.com/2078-2489/16/12/1034/pdf?version=1764215229","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"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":"Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2078-2489/16/12/1034/pdf?version=1764215229","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000187410","display_name":"Tommaso Costa","orcid":"https://orcid.org/0000-0002-0822-862X"},"institutions":[{"id":"https://openalex.org/I4210113153","display_name":"Neuroscience Institute","ror":"https://ror.org/0240rwx68","country_code":"IT","type":"facility","lineage":["https://openalex.org/I4210113153","https://openalex.org/I4210155236"]},{"id":"https://openalex.org/I4210114421","display_name":"Ospedale Koelliker","ror":"https://ror.org/028jmfg90","country_code":"IT","type":"healthcare","lineage":["https://openalex.org/I4210114421"]},{"id":"https://openalex.org/I55143463","display_name":"University of Turin","ror":"https://ror.org/048tbm396","country_code":"IT","type":"education","lineage":["https://openalex.org/I55143463"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Tommaso Costa","raw_affiliation_strings":["FOCUS Laboratory, Department of Psychology, University of Turin, 10124 Turin, Italy","GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, 10124 Turin, Italy","Neuroscience Institute of Turin (NIT), 10124 Turin, Italy"],"raw_orcid":"https://orcid.org/0000-0002-0822-862X","affiliations":[{"raw_affiliation_string":"FOCUS Laboratory, Department of Psychology, University of Turin, 10124 Turin, Italy","institution_ids":["https://openalex.org/I55143463"]},{"raw_affiliation_string":"GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, 10124 Turin, Italy","institution_ids":["https://openalex.org/I4210114421"]},{"raw_affiliation_string":"Neuroscience Institute of Turin (NIT), 10124 Turin, Italy","institution_ids":["https://openalex.org/I4210113153"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108078399","display_name":"Mario Ferraro","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114421","display_name":"Ospedale Koelliker","ror":"https://ror.org/028jmfg90","country_code":"IT","type":"healthcare","lineage":["https://openalex.org/I4210114421"]},{"id":"https://openalex.org/I55143463","display_name":"University of Turin","ror":"https://ror.org/048tbm396","country_code":"IT","type":"education","lineage":["https://openalex.org/I55143463"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Mario Ferraro","raw_affiliation_strings":["FOCUS Laboratory, Department of Psychology, University of Turin, 10124 Turin, Italy","GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, 10124 Turin, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FOCUS Laboratory, Department of Psychology, University of Turin, 10124 Turin, Italy","institution_ids":["https://openalex.org/I55143463"]},{"raw_affiliation_string":"GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, 10124 Turin, Italy","institution_ids":["https://openalex.org/I4210114421"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5000187410"],"corresponding_institution_ids":["https://openalex.org/I4210113153","https://openalex.org/I4210114421","https://openalex.org/I55143463"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1782},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1782},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27799425,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":"12","first_page":"1034","last_page":"1034"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.1777999997138977,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.1777999997138977,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T13283","display_name":"Mental Health Research Topics","score":0.14740000665187836,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10206","display_name":"Meta-analysis and systematic reviews","score":0.07810000330209732,"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/bayesian-probability","display_name":"Bayesian probability","score":0.5539000034332275},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5083000063896179},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5011000037193298},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.4562999904155731},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4465000033378601},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.44029998779296875},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.43369999527931213},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.40689998865127563},{"id":"https://openalex.org/keywords/clarity","display_name":"CLARITY","score":0.38679999113082886}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6736999750137329},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5539000034332275},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5083000063896179},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5011000037193298},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4672999978065491},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4578000009059906},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.4562999904155731},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4465000033378601},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.44029998779296875},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.43369999527931213},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4278999865055084},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.40689998865127563},{"id":"https://openalex.org/C2777146004","wikidata":"https://www.wikidata.org/wiki/Q14949826","display_name":"CLARITY","level":2,"score":0.38679999113082886},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.364300012588501},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.3537999987602234},{"id":"https://openalex.org/C2780069185","wikidata":"https://www.wikidata.org/wiki/Q7977945","display_name":"Equivalence (formal languages)","level":2,"score":0.33980000019073486},{"id":"https://openalex.org/C101112237","wikidata":"https://www.wikidata.org/wiki/Q4874481","display_name":"Bayesian statistics","level":4,"score":0.33160001039505005},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.32829999923706055},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.3197999894618988},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.3086000084877014},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.30630001425743103},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.30379998683929443},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.28859999775886536},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.28690001368522644},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C166088908","wikidata":"https://www.wikidata.org/wiki/Q308495","display_name":"Abductive reasoning","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.26660001277923584}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/info16121034","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16121034","pdf_url":"https://www.mdpi.com/2078-2489/16/12/1034/pdf?version=1764215229","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"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":"Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2d90251bfd22494ca8119aed4a1fa444","is_oa":true,"landing_page_url":"https://doaj.org/article/2d90251bfd22494ca8119aed4a1fa444","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Information, Vol 16, Iss 12, p 1034 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/info16121034","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16121034","pdf_url":"https://www.mdpi.com/2078-2489/16/12/1034/pdf?version=1764215229","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"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":"Information","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416765798.pdf","grobid_xml":"https://content.openalex.org/works/W4416765798.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W263845233","https://openalex.org/W1897139626","https://openalex.org/W1974423219","https://openalex.org/W1992536060","https://openalex.org/W1995453127","https://openalex.org/W2143891888","https://openalex.org/W2144981148","https://openalex.org/W2150291618","https://openalex.org/W2159198921","https://openalex.org/W2161498332","https://openalex.org/W2570760970","https://openalex.org/W2794100094","https://openalex.org/W2905472553","https://openalex.org/W2963062793","https://openalex.org/W2985923507","https://openalex.org/W3023338115","https://openalex.org/W3106889297","https://openalex.org/W4248681815","https://openalex.org/W4399608067"],"related_works":[],"abstract_inverted_index":{"Exchangeability":[0],"is":[1,185],"a":[2,23,140,167,188,192],"foundational":[3],"concept":[4],"in":[5,34,123,132,222],"Bayesian":[6,63,178,220],"statistics,":[7],"crucial":[8],"for":[9,28,117,214],"ensuring":[10],"the":[11,30,35,109,124,163,173,197,203],"validity":[12],"and":[13,25,46,65,76,93,100,112,119,136,149,175,199,211,224],"generalizability":[14],"of":[15,32,37,128,177,202],"inferences":[16],"from":[17],"experimental":[18],"data.":[19,125,204],"This":[20,205],"paper":[21],"presents":[22],"theoretical":[24,85,134],"computational":[26,106],"framework":[27,142,206],"understanding":[29],"role":[31],"exchangeability":[33,59,118,158,184],"reliability":[36,174],"scientific":[38],"conclusions,":[39],"with":[40],"specific":[41],"reference":[42],"to":[43,56,73,84,91,156,160,217],"psychology,":[44],"neuroimaging,":[45],"clinical":[47],"trials.":[48],"We":[49,103],"build":[50],"on":[51],"de":[52,145],"Finetti\u2019s":[53,146],"representation":[54,147],"theorem":[55,148],"show":[57],"how":[58,68],"enables":[60],"using":[61],"hierarchical":[62,101],"models,":[64],"we":[66,87],"analyze":[67],"its":[69],"violation":[70],"can":[71],"lead":[72],"interpretative":[74],"errors":[75],"paradoxes,":[77],"such":[78],"as":[79,108],"Simpson\u2019s":[80],"Paradox.":[81],"In":[82],"addition":[83],"discussion,":[86],"present":[88],"practical":[89],"strategies":[90],"evaluate":[92,157],"enforce":[94],"exchangeability,":[95],"including":[96],"randomization,":[97],"matching,":[98],"stratification,":[99],"modeling.":[102],"also":[104],"introduce":[105],"tools\u2014such":[107],"Shuffle":[110],"Test":[111],"Stratified":[113],"Bootstrap\u2014to":[114],"empirically":[115],"test":[116],"detect":[120],"latent":[121],"structures":[122],"The":[126],"novelty":[127],"this":[129],"work":[130],"lies":[131],"unifying":[133],"reasoning":[135],"empirical":[137],"testing":[138],"within":[139],"single":[141],"that":[143,171,183,195],"bridges":[144],"resampling-based":[150],"diagnostics.":[151],"By":[152],"providing":[153],"concrete":[154],"tools":[155,213],"prior":[159],"model":[161],"fitting,":[162],"proposed":[164],"approach":[165],"introduces":[166],"pre-analysis":[168],"verification":[169],"step":[170],"strengthens":[172],"transparency":[176],"inference.":[179],"Our":[180],"results":[181],"emphasize":[182],"not":[186],"merely":[187],"technical":[189],"assumption,":[190],"but":[191],"structural":[193],"property":[194],"governs":[196],"coherence":[198],"informational":[200],"integrity":[201],"provides":[207],"both":[208],"conceptual":[209],"clarity":[210],"operational":[212],"researchers":[215],"aiming":[216],"perform":[218],"robust":[219],"inference":[221],"complex":[223],"heterogeneous":[225],"datasets.":[226]},"counts_by_year":[],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-11-28T00:00:00"}
