{"id":"https://openalex.org/W2945303796","doi":"https://doi.org/10.3390/make1020039","title":"Large-Scale Simultaneous Inference with Hypothesis Testing: Multiple Testing Procedures in Practice","display_name":"Large-Scale Simultaneous Inference with Hypothesis Testing: Multiple Testing Procedures in Practice","publication_year":2019,"publication_date":"2019-05-15","ids":{"openalex":"https://openalex.org/W2945303796","doi":"https://doi.org/10.3390/make1020039","mag":"2945303796"},"language":"en","primary_location":{"id":"doi:10.3390/make1020039","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make1020039","pdf_url":"https://www.mdpi.com/2504-4990/1/2/39/pdf?version=1557926482","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"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":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2504-4990/1/2/39/pdf?version=1557926482","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057625030","display_name":"Frank Emmert\u2010Streib","orcid":"https://orcid.org/0000-0003-0745-5641"},"institutions":[{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]}],"countries":["FI"],"is_corresponding":true,"raw_author_name":"Frank Emmert-Streib","raw_affiliation_strings":["Institute of Biosciences and Medical Technology, 33520 Tampere, Finland","Predictive Society and Data Analytics Lab, Faculty of Information Technology and Communication Sciences, Tampere University, 33100 Tampere, Finland"],"raw_orcid":"https://orcid.org/0000-0003-0745-5641","affiliations":[{"raw_affiliation_string":"Institute of Biosciences and Medical Technology, 33520 Tampere, Finland","institution_ids":[]},{"raw_affiliation_string":"Predictive Society and Data Analytics Lab, Faculty of Information Technology and Communication Sciences, Tampere University, 33100 Tampere, Finland","institution_ids":["https://openalex.org/I166825849"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044244385","display_name":"Matthias Dehmer","orcid":"https://orcid.org/0000-0001-8454-5857"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]},{"id":"https://openalex.org/I4210114246","display_name":"UMIT - Private Universit\u00e4t f\u00fcr Gesundheitswissenschaften, Medizinische Informatik und Technik","ror":"https://ror.org/02d0kps43","country_code":"AT","type":"education","lineage":["https://openalex.org/I4210114246"]},{"id":"https://openalex.org/I4210136249","display_name":"University of Applied Sciences Upper Austria","ror":"https://ror.org/03jqp6d56","country_code":"AT","type":"education","lineage":["https://openalex.org/I4210136249"]}],"countries":["AT","CN"],"is_corresponding":false,"raw_author_name":"Matthias Dehmer","raw_affiliation_strings":["College of Computer and Control Engineering, Nankai University, Tianjin 300071, China","Department of Mechatronics and Biomedical Computer Science, University for Health Sciences, Medical Informatics and Technology, Tirol 6060, Austria","Institute for Intelligent Production, Faculty for Management, University of Applied Sciences Upper Austria, Steyr Campus, Steyr 4400, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer and Control Engineering, Nankai University, Tianjin 300071, China","institution_ids":["https://openalex.org/I205237279"]},{"raw_affiliation_string":"Department of Mechatronics and Biomedical Computer Science, University for Health Sciences, Medical Informatics and Technology, Tirol 6060, Austria","institution_ids":["https://openalex.org/I4210114246"]},{"raw_affiliation_string":"Institute for Intelligent Production, Faculty for Management, University of Applied Sciences Upper Austria, Steyr Campus, Steyr 4400, Austria","institution_ids":["https://openalex.org/I4210136249"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5057625030"],"corresponding_institution_ids":["https://openalex.org/I166825849"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":1.9079,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.87244291,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"1","issue":"2","first_page":"653","last_page":"683"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.9993000030517578,"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/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.9993000030517578,"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":0.9941999912261963,"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/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9832000136375427,"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/multiple-comparisons-problem","display_name":"Multiple comparisons problem","score":0.7396876811981201},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.6935736536979675},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6760069131851196},{"id":"https://openalex.org/keywords/false-discovery-rate","display_name":"False discovery rate","score":0.6292852759361267},{"id":"https://openalex.org/keywords/type-i-and-type-ii-errors","display_name":"Type I and type II errors","score":0.6211296319961548},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.579276978969574},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.5069358944892883},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4968169033527374},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.459902286529541},{"id":"https://openalex.org/keywords/null-hypothesis","display_name":"Null hypothesis","score":0.44613248109817505},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.43476593494415283},{"id":"https://openalex.org/keywords/principal","display_name":"Principal (computer security)","score":0.4317278563976288},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43071454763412476},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.36131787300109863},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35169193148612976},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2341979444026947}],"concepts":[{"id":"https://openalex.org/C183905921","wikidata":"https://www.wikidata.org/wiki/Q1038757","display_name":"Multiple comparisons problem","level":2,"score":0.7396876811981201},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.6935736536979675},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6760069131851196},{"id":"https://openalex.org/C193244246","wikidata":"https://www.wikidata.org/wiki/Q5432696","display_name":"False discovery rate","level":3,"score":0.6292852759361267},{"id":"https://openalex.org/C40696583","wikidata":"https://www.wikidata.org/wiki/Q989120","display_name":"Type I and type II errors","level":2,"score":0.6211296319961548},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.579276978969574},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.5069358944892883},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4968169033527374},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.459902286529541},{"id":"https://openalex.org/C191988596","wikidata":"https://www.wikidata.org/wiki/Q628374","display_name":"Null hypothesis","level":2,"score":0.44613248109817505},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.43476593494415283},{"id":"https://openalex.org/C144559511","wikidata":"https://www.wikidata.org/wiki/Q2986279","display_name":"Principal (computer security)","level":2,"score":0.4317278563976288},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43071454763412476},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.36131787300109863},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35169193148612976},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2341979444026947},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/make1020039","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make1020039","pdf_url":"https://www.mdpi.com/2504-4990/1/2/39/pdf?version=1557926482","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"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":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},{"id":"pmh:oai:mdpi.com:/2504-4990/1/2/39/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/make1020039","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/make1020039","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make1020039","pdf_url":"https://www.mdpi.com/2504-4990/1/2/39/pdf?version=1557926482","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"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":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2945303796.pdf","grobid_xml":"https://content.openalex.org/works/W2945303796.grobid-xml"},"referenced_works_count":98,"referenced_works":["https://openalex.org/W17046467","https://openalex.org/W1001370459","https://openalex.org/W1492486975","https://openalex.org/W1510659740","https://openalex.org/W1519128746","https://openalex.org/W1531856863","https://openalex.org/W1590047728","https://openalex.org/W1596515083","https://openalex.org/W1726463755","https://openalex.org/W1891298814","https://openalex.org/W1965138864","https://openalex.org/W1969309399","https://openalex.org/W1970047903","https://openalex.org/W1976954310","https://openalex.org/W1980361506","https://openalex.org/W1985918072","https://openalex.org/W1997917263","https://openalex.org/W2002420618","https://openalex.org/W2002947007","https://openalex.org/W2003842689","https://openalex.org/W2010348162","https://openalex.org/W2011550781","https://openalex.org/W2019634045","https://openalex.org/W2019880039","https://openalex.org/W2023045360","https://openalex.org/W2024105897","https://openalex.org/W2029084939","https://openalex.org/W2029293261","https://openalex.org/W2030999406","https://openalex.org/W2036714085","https://openalex.org/W2037586880","https://openalex.org/W2043045839","https://openalex.org/W2045638068","https://openalex.org/W2049331221","https://openalex.org/W2057758736","https://openalex.org/W2076684951","https://openalex.org/W2078556927","https://openalex.org/W2087651612","https://openalex.org/W2090343642","https://openalex.org/W2092793370","https://openalex.org/W2094411422","https://openalex.org/W2095144378","https://openalex.org/W2099107563","https://openalex.org/W2099657218","https://openalex.org/W2101759642","https://openalex.org/W2102122784","https://openalex.org/W2105381419","https://openalex.org/W2110065044","https://openalex.org/W2111748423","https://openalex.org/W2113175552","https://openalex.org/W2113381189","https://openalex.org/W2114060717","https://openalex.org/W2115012618","https://openalex.org/W2116319049","https://openalex.org/W2120446809","https://openalex.org/W2121044470","https://openalex.org/W2133229226","https://openalex.org/W2134696273","https://openalex.org/W2135445066","https://openalex.org/W2141975087","https://openalex.org/W2143079975","https://openalex.org/W2143156387","https://openalex.org/W2146273335","https://openalex.org/W2147752708","https://openalex.org/W2156909104","https://openalex.org/W2171160963","https://openalex.org/W2294962740","https://openalex.org/W2490447578","https://openalex.org/W2609501202","https://openalex.org/W2738587025","https://openalex.org/W2765243560","https://openalex.org/W2796856748","https://openalex.org/W2808424220","https://openalex.org/W2905506148","https://openalex.org/W2912102502","https://openalex.org/W2937765800","https://openalex.org/W3047398590","https://openalex.org/W3099699172","https://openalex.org/W3101633035","https://openalex.org/W3103223646","https://openalex.org/W3103280585","https://openalex.org/W3103900655","https://openalex.org/W3105361009","https://openalex.org/W3106097685","https://openalex.org/W3122448928","https://openalex.org/W3122976065","https://openalex.org/W3123267262","https://openalex.org/W3123745421","https://openalex.org/W3124195593","https://openalex.org/W4205210034","https://openalex.org/W4232206722","https://openalex.org/W4317568391","https://openalex.org/W6653223086","https://openalex.org/W6676591658","https://openalex.org/W6678230397","https://openalex.org/W6681418224","https://openalex.org/W6682081145","https://openalex.org/W7067803176"],"related_works":["https://openalex.org/W154531455","https://openalex.org/W2113330311","https://openalex.org/W2057633723","https://openalex.org/W2046875666","https://openalex.org/W2106547200","https://openalex.org/W1995992573","https://openalex.org/W2889978286","https://openalex.org/W200550325","https://openalex.org/W3135758431","https://openalex.org/W104021676"],"abstract_inverted_index":{"A":[0],"statistical":[1,59],"hypothesis":[2,60],"test":[3,65],"is":[4],"one":[5],"of":[6,21,32,50,67,100,136],"the":[7,18,30,64,68,104,120,125,187],"most":[8,102],"eminent":[9],"methods":[10,191],"in":[11,43,82],"statistics.":[12],"Its":[13],"pivotal":[14],"role":[15],"comes":[16],"from":[17],"wide":[19],"range":[20],"practical":[22],"problems":[23],"it":[24,40,54],"can":[25,165],"be":[26],"applied":[27,73],"to":[28,45,56,63,78,96],"and":[29,149],"sparsity":[31],"data":[33,52,168,176,195],"requirements.":[34],"Being":[35],"an":[36,79],"unsupervised":[37],"method":[38],"makes":[39,53],"very":[41],"flexible":[42],"adapting":[44],"real-world":[46,175],"situations.":[47],"The":[48],"availability":[49],"high-dimensional":[51],"necessary":[55],"apply":[57],"such":[58],"tests":[61],"simultaneously":[62],"statistics":[66],"underlying":[69],"covariates.":[70],"However,":[71],"if":[72],"without":[74],"correction":[75],"this":[76,88,109],"leads":[77],"inevitable":[80],"increase":[81],"Type":[83,105],"1":[84,106],"errors.":[85],"To":[86],"counteract":[87],"effect,":[89],"multiple":[90,114,154],"testing":[91,115,155],"procedures":[92,116,163],"have":[93],"been":[94],"introduced":[95],"control":[97],"various":[98],"types":[99],"errors,":[101],"notably":[103],"error.":[107],"In":[108],"paper,":[110],"we":[111,181],"review":[112],"modern":[113],"for":[117,193],"controlling":[118],"either":[119],"family-wise":[121],"error":[122],"(FWER)":[123],"or":[124],"false-discovery":[126],"rate":[127],"(FDR).":[128],"We":[129,157],"emphasize":[130],"their":[131],"principal":[132],"approach":[133],"allowing":[134],"categorization":[135],"them":[137],"as":[138],"(1)":[139],"single-step":[140],"vs.":[141,146,152],"stepwise":[142],"approaches,":[143,148],"(2)":[144],"adaptive":[145],"non-adaptive":[147],"(3)":[150],"marginal":[151],"joint":[153],"procedures.":[156],"place":[158],"a":[159,170],"particular":[160],"focus":[161],"on":[162],"that":[164],"deal":[166],"with":[167,169],"(strong)":[171],"correlation":[172],"structure":[173],"because":[174],"are":[177],"rarely":[178],"uncorrelated.":[179],"Furthermore,":[180],"also":[182],"provide":[183],"background":[184],"information":[185],"making":[186],"often":[188],"technically":[189],"intricate":[190],"accessible":[192],"interdisciplinary":[194],"scientists.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
