{"id":"https://openalex.org/W2136986719","doi":"https://doi.org/10.1002/sim.5506","title":"Flexibly modeling the baseline risk in meta\u2010analysis","display_name":"Flexibly modeling the baseline risk in meta\u2010analysis","publication_year":2012,"publication_date":"2012-07-17","ids":{"openalex":"https://openalex.org/W2136986719","doi":"https://doi.org/10.1002/sim.5506","mag":"2136986719","pmid":"https://pubmed.ncbi.nlm.nih.gov/22807131"},"language":"en","primary_location":{"id":"doi:10.1002/sim.5506","doi":"https://doi.org/10.1002/sim.5506","is_oa":false,"landing_page_url":"https://doi.org/10.1002/sim.5506","pdf_url":null,"source":{"id":"https://openalex.org/S55189604","display_name":"Statistics in Medicine","issn_l":"0277-6715","issn":["0277-6715","1097-0258"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","dongbi-b","doyens","jufo-2","ki-jl-2","medline","norway-2","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics in Medicine","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","pubmed"],"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/A5069664241","display_name":"Annamaria Guolo","orcid":"https://orcid.org/0000-0002-6873-4372","observed_orcids":["https://orcid.org/0000-0002-6873-4372"]},"institutions":[{"id":"https://openalex.org/I119439378","display_name":"University of Verona","ror":"https://ror.org/039bp8j42","country_code":"IT","type":"education","lineage":["https://openalex.org/I119439378"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"A. Guolo","raw_affiliation_strings":["Department of Economics, University of Verona, Via dell'Artigliere 19, I-37129 Verona, Italy","A. Guolo, Department of Economics, University of Verona, Via dell'Artigliere 19, I-37129, Verona, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Economics, University of Verona, Via dell'Artigliere 19, I-37129 Verona, Italy","institution_ids":["https://openalex.org/I119439378"]},{"raw_affiliation_string":"A. Guolo, Department of Economics, University of Verona, Via dell'Artigliere 19, I-37129, Verona, Italy","institution_ids":["https://openalex.org/I119439378"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5069664241"],"corresponding_institution_ids":["https://openalex.org/I119439378"],"apc_list":{"value":5450,"currency":"USD","value_usd":5450},"apc_paid":null,"fwci":2.3589,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.89581131,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":96},"biblio":{"volume":"32","issue":"1","first_page":"40","last_page":"50"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10206","display_name":"Meta-analysis and systematic reviews","score":0.8687000274658203,"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"}},"topics":[{"id":"https://openalex.org/T10206","display_name":"Meta-analysis and systematic reviews","score":0.8687000274658203,"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"}},{"id":"https://openalex.org/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.10949999839067459,"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":0.007000000216066837,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/baseline-risk","display_name":"baseline risk","score":0.9520000219345093},{"id":"https://openalex.org/keywords/meta-analysis","display_name":"meta-analysis","score":0.746999979019165},{"id":"https://openalex.org/keywords/skew-normal-distribution","display_name":"skew-normal distribution","score":0.8859999775886536},{"id":"https://openalex.org/keywords/likelihood-based-inference","display_name":"likelihood-based inference","score":0.7870000004768372},{"id":"https://openalex.org/keywords/clinical-trials","display_name":"clinical trials","score":0.5820000171661377},{"id":"https://openalex.org/keywords/treatment-heterogeneity","display_name":"treatment effect heterogeneity","score":0.640999972820282},{"id":"https://openalex.org/keywords/measurement-error","display_name":"measurement error","score":0.5860000252723694},{"id":"https://openalex.org/keywords/weighted-least-squares","display_name":"weighted least squares","score":0.8859999775886536},{"id":"https://openalex.org/keywords/normality-assumption","display_name":"normality assumption","score":0.5989999771118164}],"concepts":[{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.801214873790741},{"id":"https://openalex.org/C2776157432","wikidata":"https://www.wikidata.org/wiki/Q1375683","display_name":"Normality","level":2,"score":0.5424152612686157},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5138623714447021},{"id":"https://openalex.org/C43711488","wikidata":"https://www.wikidata.org/wiki/Q7534783","display_name":"Skew","level":2,"score":0.5032314658164978},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48283180594444275},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.46448880434036255},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4639897346496582},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4135090708732605},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29024046659469604},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1606907844543457},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000924","descriptor_name":"Anticholesteremic Agents","qualifier_ui":"Q000627","qualifier_name":"therapeutic use","is_major_topic":false},{"descriptor_ui":"D000959","descriptor_name":"Antihypertensive Agents","qualifier_ui":"Q000627","qualifier_name":"therapeutic use","is_major_topic":false},{"descriptor_ui":"D002318","descriptor_name":"Cardiovascular Diseases","qualifier_ui":"Q000188","qualifier_name":"drug therapy","is_major_topic":false},{"descriptor_ui":"D002318","descriptor_name":"Cardiovascular Diseases","qualifier_ui":"Q000401","qualifier_name":"mortality","is_major_topic":false},{"descriptor_ui":"D002784","descriptor_name":"Cholesterol","qualifier_ui":"Q000097","qualifier_name":"blood","is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012306","descriptor_name":"Risk","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015201","descriptor_name":"Meta-Analysis as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016013","descriptor_name":"Likelihood Functions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":3,"locations":[{"id":"doi:10.1002/sim.5506","doi":"https://doi.org/10.1002/sim.5506","is_oa":false,"landing_page_url":"https://doi.org/10.1002/sim.5506","pdf_url":null,"source":{"id":"https://openalex.org/S55189604","display_name":"Statistics in Medicine","issn_l":"0277-6715","issn":["0277-6715","1097-0258"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","dongbi-b","doyens","jufo-2","ki-jl-2","medline","norway-2","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics in Medicine","raw_type":"journal-article"},{"id":"pmid:22807131","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/22807131","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics in medicine","raw_type":"Comparative Study"},{"id":"pmh:oai:www.research.unipd.it:11577/3160993","doi":null,"is_oa":false,"landing_page_url":"http://hdl.handle.net/11577/3160993","pdf_url":null,"source":{"id":"https://openalex.org/S4306402547","display_name":"Padua Research Archive (University of Padova)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I138689650","host_organization_name":"University of Padua","host_organization_lineage":["https://openalex.org/I138689650"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.5683000087738037}],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320331528","display_name":"Ministero dell'Universit\u00e0 e della Ricerca","ror":"https://ror.org/0341vw408"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W94194614","https://openalex.org/W1639275303","https://openalex.org/W1986306452","https://openalex.org/W1988769265","https://openalex.org/W2001855995","https://openalex.org/W2019457874","https://openalex.org/W2030553221","https://openalex.org/W2039076379","https://openalex.org/W2056083953","https://openalex.org/W2062827125","https://openalex.org/W2080191652","https://openalex.org/W2086705478","https://openalex.org/W2090597068","https://openalex.org/W2095703955","https://openalex.org/W2098288181","https://openalex.org/W2099610513","https://openalex.org/W2100170944","https://openalex.org/W2113099921","https://openalex.org/W2126602143","https://openalex.org/W2148678270","https://openalex.org/W2151133465","https://openalex.org/W2161920977","https://openalex.org/W2163102936","https://openalex.org/W2163364967","https://openalex.org/W2167497124","https://openalex.org/W4237374278","https://openalex.org/W4249596886","https://openalex.org/W4302338619"],"related_works":["https://openalex.org/W2019457874","https://openalex.org/W2163364967","https://openalex.org/W2100170944","https://openalex.org/W4415468397","https://openalex.org/W3130836055","https://openalex.org/W7081708070","https://openalex.org/W2380629011","https://openalex.org/W2151133465","https://openalex.org/W2104373766","https://openalex.org/W2132090482"],"abstract_inverted_index":{"This":[0],"paper":[1],"investigates":[2],"a":[3,58],"likelihood-based":[4],"approach":[5,19,83,94],"in":[6],"meta-analysis":[7],"of":[8,22,28,42,61,81,120],"clinical":[9],"trials":[10],"involving":[11],"the":[12,23,26,30,34,39,43,54,65,79,82,91,97,102,108,114,118],"baseline":[13,35,44,55,103],"risk":[14,45,56,104],"as":[15],"explanatory":[16],"variable.":[17],"The":[18,86],"takes":[20],"account":[21],"errors":[24],"affecting":[25],"measure":[27],"either":[29],"treatment":[31],"effect":[32],"or":[33],"risk,":[36],"while":[37],"facing":[38],"potential":[40],"misspecification":[41],"distribution.":[46],"To":[47],"this":[48,75],"aim,":[49],"we":[50],"suggest":[51],"to":[52,70,117],"model":[53],"through":[57,84],"flexible":[59],"family":[60],"distributions":[62],"represented":[63],"by":[64],"skew-normal.":[66],"We":[67,112],"describe":[68],"how":[69],"carry":[71],"out":[72],"inference":[73],"within":[74],"framework":[76],"and":[77,106],"evaluate":[78],"performance":[80],"simulation.":[85],"method":[87],"is":[88],"compared":[89],"with":[90,107],"routine":[92],"likelihood":[93],"based":[95],"on":[96],"restrictive":[98],"normality":[99],"assumption":[100],"for":[101],"distribution":[105],"weighted":[109],"least-squares":[110],"regression.":[111],"apply":[113],"competing":[115],"approaches":[116],"analysis":[119],"two":[121],"published":[122],"datasets.":[123]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}