{"id":"https://openalex.org/W4387369779","doi":"https://doi.org/10.7717/peerj-cs.1620","title":"Comparison between pystan and numpyro in Bayesian item response theory: evaluation of agreement of estimated latent parameters and sampling performance","display_name":"Comparison between pystan and numpyro in Bayesian item response theory: evaluation of agreement of estimated latent parameters and sampling performance","publication_year":2023,"publication_date":"2023-10-05","ids":{"openalex":"https://openalex.org/W4387369779","doi":"https://doi.org/10.7717/peerj-cs.1620","pmid":"https://pubmed.ncbi.nlm.nih.gov/37869462"},"language":"en","primary_location":{"id":"doi:10.7717/peerj-cs.1620","is_oa":true,"landing_page_url":"https://doi.org/10.7717/peerj-cs.1620","pdf_url":"https://peerj.com/articles/cs-1620.pdf","source":{"id":"https://openalex.org/S4210178049","display_name":"PeerJ Computer Science","issn_l":"2376-5992","issn":["2376-5992"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320104","host_organization_name":"PeerJ, Inc.","host_organization_lineage":["https://openalex.org/P4310320104"],"host_organization_lineage_names":["PeerJ, Inc."],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PeerJ Computer Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://peerj.com/articles/cs-1620.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066648889","display_name":"Mizuho Nishio","orcid":"https://orcid.org/0000-0001-5870-0868"},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"education","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Mizuho Nishio","raw_affiliation_strings":["Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan","institution_ids":["https://openalex.org/I65837984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079758209","display_name":"Eiji Ota","orcid":null},"institutions":[{"id":"https://openalex.org/I88302906","display_name":"Futaba (Japan)","ror":"https://ror.org/03b6zzt23","country_code":"JP","type":"company","lineage":["https://openalex.org/I88302906"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Eiji Ota","raw_affiliation_strings":["Futaba Numerical Technologies, Iruma, Japan"],"affiliations":[{"raw_affiliation_string":"Futaba Numerical Technologies, Iruma, Japan","institution_ids":["https://openalex.org/I88302906"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014730894","display_name":"Hidetoshi Matsuo","orcid":"https://orcid.org/0000-0002-9684-4632"},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"education","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hidetoshi Matsuo","raw_affiliation_strings":["Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan","institution_ids":["https://openalex.org/I65837984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016277373","display_name":"Takaaki Matsunaga","orcid":null},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"education","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takaaki Matsunaga","raw_affiliation_strings":["Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan","institution_ids":["https://openalex.org/I65837984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070197405","display_name":"Aki Miyazaki","orcid":"https://orcid.org/0009-0007-0603-8308"},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"education","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Aki Miyazaki","raw_affiliation_strings":["Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan","institution_ids":["https://openalex.org/I65837984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003394557","display_name":"Takamichi Murakami","orcid":"https://orcid.org/0000-0001-7782-548X"},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"education","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takamichi Murakami","raw_affiliation_strings":["Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan","institution_ids":["https://openalex.org/I65837984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5066648889"],"corresponding_institution_ids":["https://openalex.org/I65837984"],"apc_list":{"value":1395,"currency":"USD","value_usd":1395},"apc_paid":{"value":1395,"currency":"USD","value_usd":1395},"fwci":1.0042,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.78393683,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"9","issue":null,"first_page":"e1620","last_page":"e1620"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9908000230789185,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9908000230789185,"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/T10467","display_name":"Psychometric Methodologies and Testing","score":0.9861000180244446,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"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/T12011","display_name":"Insurance, Mortality, Demography, Risk Management","score":0.9847000241279602,"subfield":{"id":"https://openalex.org/subfields/3317","display_name":"Demography"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.8268674612045288},{"id":"https://openalex.org/keywords/item-response-theory","display_name":"Item response theory","score":0.6908473968505859},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5626937747001648},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.535994827747345},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.47060781717300415},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.45600593090057373},{"id":"https://openalex.org/keywords/bayesian-statistics","display_name":"Bayesian statistics","score":0.43958523869514465},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.41347506642341614},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.3028636574745178},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27252644300460815},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24978947639465332},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.17046618461608887},{"id":"https://openalex.org/keywords/psychometrics","display_name":"Psychometrics","score":0.06477239727973938}],"concepts":[{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.8268674612045288},{"id":"https://openalex.org/C19875794","wikidata":"https://www.wikidata.org/wiki/Q1207340","display_name":"Item response theory","level":3,"score":0.6908473968505859},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5626937747001648},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.535994827747345},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.47060781717300415},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.45600593090057373},{"id":"https://openalex.org/C101112237","wikidata":"https://www.wikidata.org/wiki/Q4874481","display_name":"Bayesian statistics","level":4,"score":0.43958523869514465},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.41347506642341614},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.3028636574745178},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27252644300460815},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24978947639465332},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.17046618461608887},{"id":"https://openalex.org/C171606756","wikidata":"https://www.wikidata.org/wiki/Q506132","display_name":"Psychometrics","level":2,"score":0.06477239727973938}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.7717/peerj-cs.1620","is_oa":true,"landing_page_url":"https://doi.org/10.7717/peerj-cs.1620","pdf_url":"https://peerj.com/articles/cs-1620.pdf","source":{"id":"https://openalex.org/S4210178049","display_name":"PeerJ Computer Science","issn_l":"2376-5992","issn":["2376-5992"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320104","host_organization_name":"PeerJ, Inc.","host_organization_lineage":["https://openalex.org/P4310320104"],"host_organization_lineage_names":["PeerJ, Inc."],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PeerJ Computer Science","raw_type":"journal-article"},{"id":"pmid:37869462","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37869462","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,"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":"PeerJ. Computer science","raw_type":null},{"id":"pmh:oai:da.lib.kobe-u.ac.jp:20.500.14094/0100483376","is_oa":true,"landing_page_url":"https://hdl.handle.net/20.500.14094/0100483376","pdf_url":"https://da.lib.kobe-u.ac.jp/da/kernel/0100483376/0100483376.pdf","source":{"id":"https://openalex.org/S4306401924","display_name":"Kobe University Repository Kernel (Kobe University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I65837984","host_organization_name":"Kobe University","host_organization_lineage":["https://openalex.org/I65837984"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"PeerJ Computer Science\u30009, e1620","raw_type":"journal article"},{"id":"pmh:oai:pubmedcentral.nih.gov:10588711","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10588711","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10588711/pdf/peerj-cs-09-1620.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"PeerJ Comput Sci","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:bc7948afa2a44042a80fcef8d28a9e9e","is_oa":true,"landing_page_url":"https://doaj.org/article/bc7948afa2a44042a80fcef8d28a9e9e","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"PeerJ Computer Science, Vol 9, p e1620 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.7717/peerj-cs.1620","is_oa":true,"landing_page_url":"https://doi.org/10.7717/peerj-cs.1620","pdf_url":"https://peerj.com/articles/cs-1620.pdf","source":{"id":"https://openalex.org/S4210178049","display_name":"PeerJ Computer Science","issn_l":"2376-5992","issn":["2376-5992"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320104","host_organization_name":"PeerJ, Inc.","host_organization_lineage":["https://openalex.org/P4310320104"],"host_organization_lineage_names":["PeerJ, Inc."],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PeerJ Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1069223013","display_name":null,"funder_award_id":"JSPS KAKENHI","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G3459562248","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G4636223006","display_name":null,"funder_award_id":"JSPS KAK","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G8430481527","display_name":null,"funder_award_id":"Number","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G8481511107","display_name":null,"funder_award_id":"23K17229","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G8804604710","display_name":null,"funder_award_id":"22K07665","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387369779.pdf","grobid_xml":"https://content.openalex.org/works/W4387369779.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W1969055757","https://openalex.org/W1993807570","https://openalex.org/W2071373556","https://openalex.org/W2092722444","https://openalex.org/W2313339984","https://openalex.org/W2328906200","https://openalex.org/W2508123183","https://openalex.org/W2577537660","https://openalex.org/W2591197289","https://openalex.org/W2947731626","https://openalex.org/W2981150028","https://openalex.org/W3156138366","https://openalex.org/W4248681815","https://openalex.org/W4249332350","https://openalex.org/W4311288581","https://openalex.org/W4361300644","https://openalex.org/W6769403462"],"related_works":["https://openalex.org/W3087071515","https://openalex.org/W4283077537","https://openalex.org/W2999603699","https://openalex.org/W2902858271","https://openalex.org/W2464065341","https://openalex.org/W2947536360","https://openalex.org/W3086697448","https://openalex.org/W1987558550","https://openalex.org/W4302573481","https://openalex.org/W2505308168"],"abstract_inverted_index":{"Numpyro":[0],"and":[1,10,23],"pystan":[2],"were":[3],"useful":[4],"for":[5],"applying":[6],"the":[7,16,29,35],"Bayesian":[8],"1PL-IRT":[9],"2PL-IRT.":[11],"Our":[12],"results":[13],"show":[14],"that":[15,24],"two":[17],"libraries":[18,31],"yielded":[19],"similar":[20],"estimation":[21],"result":[22],"regarding":[25],"to":[26],"sampling":[27],"time,":[28],"fastest":[30],"differed":[32],"based":[33],"on":[34],"dataset":[36],"size.":[37]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
