{"id":"https://openalex.org/W4362508293","doi":"https://doi.org/10.48550/arxiv.2303.17731","title":"$\u03b2^{4}$-IRT: A New $\u03b2^{3}$-IRT with Enhanced Discrimination Estimation","display_name":"$\u03b2^{4}$-IRT: A New $\u03b2^{3}$-IRT with Enhanced Discrimination Estimation","publication_year":2023,"publication_date":"2023-03-30","ids":{"openalex":"https://openalex.org/W4362508293","doi":"https://doi.org/10.48550/arxiv.2303.17731"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2303.17731","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2303.17731","pdf_url":"https://arxiv.org/pdf/2303.17731","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2303.17731","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059560678","display_name":"Manuel Ferreira-Junior","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ferreira-Junior, Manuel","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034553933","display_name":"Jessica T. S. Reinaldo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Reinaldo, Jessica T. S.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077682283","display_name":"Telmo M. Silva Filho","orcid":"https://orcid.org/0000-0003-0826-6885"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Filho, Telmo M. Silva","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046523539","display_name":"Eufrasio A. Lima Neto","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Neto, Eufrasio A. Lima","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5083998049","display_name":"Ricardo B. C. Prud\u00eancio","orcid":"https://orcid.org/0000-0001-7084-1233"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Prudencio, Ricardo B. C.","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5059560678"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9786999821662903,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9786999821662903,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9502000212669373,"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"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9175999760627747,"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/item-response-theory","display_name":"Item response theory","score":0.8399193286895752},{"id":"https://openalex.org/keywords/beta-distribution","display_name":"Beta distribution","score":0.5992068648338318},{"id":"https://openalex.org/keywords/sign","display_name":"Sign (mathematics)","score":0.5617449879646301},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.473419725894928},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.47186559438705444},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.46433699131011963},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4228544235229492},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.39382752776145935},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3786069452762604},{"id":"https://openalex.org/keywords/psychometrics","display_name":"Psychometrics","score":0.17667022347450256}],"concepts":[{"id":"https://openalex.org/C19875794","wikidata":"https://www.wikidata.org/wiki/Q1207340","display_name":"Item response theory","level":3,"score":0.8399193286895752},{"id":"https://openalex.org/C21621910","wikidata":"https://www.wikidata.org/wiki/Q756254","display_name":"Beta distribution","level":2,"score":0.5992068648338318},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.5617449879646301},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.473419725894928},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.47186559438705444},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.46433699131011963},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4228544235229492},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.39382752776145935},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3786069452762604},{"id":"https://openalex.org/C171606756","wikidata":"https://www.wikidata.org/wiki/Q506132","display_name":"Psychometrics","level":2,"score":0.17667022347450256},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2303.17731","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2303.17731","pdf_url":"https://arxiv.org/pdf/2303.17731","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2303.17731","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2303.17731","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2303.17731","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2303.17731","pdf_url":"https://arxiv.org/pdf/2303.17731","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5799999833106995},{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.4099999964237213}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4362508293.pdf","grobid_xml":"https://content.openalex.org/works/W4362508293.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2562263695","https://openalex.org/W2135187896","https://openalex.org/W2147201983","https://openalex.org/W2015518264","https://openalex.org/W2795035211","https://openalex.org/W2160108762","https://openalex.org/W1718066205","https://openalex.org/W2017034551","https://openalex.org/W2163948609","https://openalex.org/W4362508293"],"abstract_inverted_index":{"Item":[0],"response":[1,26,42],"theory":[2,27],"aims":[3],"to":[4,66,85,131,144,162,169,183],"estimate":[5,67],"respondent's":[6],"latent":[7],"skills":[8],"from":[9],"their":[10],"responses":[11],"in":[12,83,216],"tests":[13],"composed":[14],"of":[15,20,24,34,56,156,213],"items":[16],"with":[17,108,112,210],"different":[18,32],"levels":[19],"difficulty.":[21],"Several":[22],"models":[23],"item":[25,105],"have":[28],"been":[29],"proposed":[30,174],"for":[31,139,177],"types":[33],"tasks,":[35],"such":[36],"as":[37,153,205],"binary":[38],"or":[39],"probabilistic":[40],"responses,":[41,45],"time,":[43],"multiple":[44],"among":[46],"others.":[47],"In":[48,71,142],"this":[49,146],"paper,":[50],"we":[51,79,148,200],"propose":[52],"a":[53,98,109,206],"new":[54,158,193],"version":[55,194],"$\u03b2^3$-IRT,":[57,72],"called":[58],"$\u03b2^{4}$-IRT,":[59],"which":[60],"uses":[61],"the":[62,68,113,119,125,133,140,150,154,163,166,170,196,211],"gradient":[63,91],"descent":[64,92],"method":[65],"model":[69],"parameters.":[70,179],"abilities":[73],"and":[74,136,165,186,191],"difficulties":[75],"are":[76],"bounded,":[77],"thus":[78],"employ":[80],"link":[81],"functions":[82],"order":[84,143],"turn":[86],"$\u03b2^{4}$-IRT":[87,185,202],"into":[88],"an":[89,104],"unconstrained":[90],"process.":[93],"The":[94],"original":[95,197],"$\u03b2^3$-IRT":[96,187,214],"had":[97],"symmetry":[99],"problem,":[100],"meaning":[101],"that,":[102],"if":[103],"was":[106],"initialised":[107],"discrimination":[110,121,135,151],"value":[111],"wrong":[114],"sign,":[115],"e.g.":[116],"negative":[117],"when":[118],"actual":[120],"should":[122],"be":[123,129],"positive,":[124],"fitting":[126],"process":[127],"could":[128],"unable":[130],"recover":[132],"correct":[134],"difficulty":[137],"values":[138],"item.":[141],"tackle":[145],"limitation,":[147],"modelled":[149],"parameter":[152,189],"product":[155],"two":[157],"parameters,":[159],"one":[160],"corresponding":[161],"sign":[164],"second":[167],"associated":[168],"magnitude.":[171],"We":[172,180],"also":[173],"sensible":[175],"priors":[176],"all":[178],"performed":[181],"experiments":[182],"compare":[184],"regarding":[188],"recovery":[190],"our":[192,217],"outperformed":[195],"$\u03b2^3$-IRT.":[198],"Finally,":[199],"made":[201],"publicly":[203],"available":[204],"Python":[207],"package,":[208],"along":[209],"implementation":[212],"used":[215],"experiments.":[218]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2023-04-06T00:00:00"}