{"id":"https://openalex.org/W4285493242","doi":"https://doi.org/10.1080/03610918.2022.2097694","title":"A multidimensional IRT model for ability-item-based guessing: the development of a two-parameter logistic extension model","display_name":"A multidimensional IRT model for ability-item-based guessing: the development of a two-parameter logistic extension model","publication_year":2022,"publication_date":"2022-07-15","ids":{"openalex":"https://openalex.org/W4285493242","doi":"https://doi.org/10.1080/03610918.2022.2097694"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2022.2097694","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2097694","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"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/A5014090180","display_name":"Youxiang Jiang","orcid":"https://orcid.org/0000-0003-4557-5038"},"institutions":[{"id":"https://openalex.org/I53592917","display_name":"Jiangxi Normal University","ror":"https://ror.org/05nkgk822","country_code":"CN","type":"education","lineage":["https://openalex.org/I53592917"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youxiang Jiang","raw_affiliation_strings":["School of Psychology, Jiangxi Normal University, Nanchang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Psychology, Jiangxi Normal University, Nanchang, China","institution_ids":["https://openalex.org/I53592917"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067954758","display_name":"Xiao-Fang Yu","orcid":"https://orcid.org/0000-0002-1933-636X"},"institutions":[{"id":"https://openalex.org/I53592917","display_name":"Jiangxi Normal University","ror":"https://ror.org/05nkgk822","country_code":"CN","type":"education","lineage":["https://openalex.org/I53592917"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaofang Yu","raw_affiliation_strings":["School of Psychology, Jiangxi Normal University, Nanchang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Psychology, Jiangxi Normal University, Nanchang, China","institution_ids":["https://openalex.org/I53592917"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101714085","display_name":"Yan Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I53592917","display_name":"Jiangxi Normal University","ror":"https://ror.org/05nkgk822","country_code":"CN","type":"education","lineage":["https://openalex.org/I53592917"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Cai","raw_affiliation_strings":["School of Psychology, Jiangxi Normal University, Nanchang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Psychology, Jiangxi Normal University, Nanchang, China","institution_ids":["https://openalex.org/I53592917"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078075518","display_name":"Dongbo Tu","orcid":"https://orcid.org/0000-0001-6091-4726"},"institutions":[{"id":"https://openalex.org/I53592917","display_name":"Jiangxi Normal University","ror":"https://ror.org/05nkgk822","country_code":"CN","type":"education","lineage":["https://openalex.org/I53592917"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dongbo Tu","raw_affiliation_strings":["School of Psychology, Jiangxi Normal University, Nanchang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Psychology, Jiangxi Normal University, Nanchang, China","institution_ids":["https://openalex.org/I53592917"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5078075518"],"corresponding_institution_ids":["https://openalex.org/I53592917"],"apc_list":null,"apc_paid":null,"fwci":0.3267,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.60855285,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"53","issue":"7","first_page":"3068","last_page":"3080"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10467","display_name":"Psychometric Methodologies and Testing","score":0.9810000061988831,"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"}},"topics":[{"id":"https://openalex.org/T10467","display_name":"Psychometric Methodologies and Testing","score":0.9810000061988831,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9789999723434448,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9556000232696533,"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/extension","display_name":"Extension (predicate logic)","score":0.6107332706451416},{"id":"https://openalex.org/keywords/item-response-theory","display_name":"Item response theory","score":0.6086789965629578},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.4960523545742035},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4535045921802521},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.40792316198349},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3775431513786316},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3315560817718506},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31942692399024963},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.26093900203704834},{"id":"https://openalex.org/keywords/psychometrics","display_name":"Psychometrics","score":0.19554099440574646}],"concepts":[{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.6107332706451416},{"id":"https://openalex.org/C19875794","wikidata":"https://www.wikidata.org/wiki/Q1207340","display_name":"Item response theory","level":3,"score":0.6086789965629578},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.4960523545742035},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4535045921802521},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.40792316198349},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3775431513786316},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3315560817718506},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31942692399024963},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26093900203704834},{"id":"https://openalex.org/C171606756","wikidata":"https://www.wikidata.org/wiki/Q506132","display_name":"Psychometrics","level":2,"score":0.19554099440574646},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2022.2097694","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2097694","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"No poverty","score":0.6299999952316284,"id":"https://metadata.un.org/sdg/1"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W124640768","https://openalex.org/W1921865210","https://openalex.org/W1964140919","https://openalex.org/W1984225473","https://openalex.org/W1992135699","https://openalex.org/W1999424009","https://openalex.org/W2006338519","https://openalex.org/W2014472327","https://openalex.org/W2057765075","https://openalex.org/W2103358435","https://openalex.org/W2123222757","https://openalex.org/W2139641046","https://openalex.org/W2142635246","https://openalex.org/W2148534890","https://openalex.org/W2168175751","https://openalex.org/W2203714058","https://openalex.org/W2577537660","https://openalex.org/W2606429215","https://openalex.org/W2787410416","https://openalex.org/W2790952335","https://openalex.org/W2893144381","https://openalex.org/W3123421154","https://openalex.org/W4246435226","https://openalex.org/W4248681815","https://openalex.org/W4399648958","https://openalex.org/W6680707143","https://openalex.org/W6736568619"],"related_works":["https://openalex.org/W2755867900","https://openalex.org/W1985339677","https://openalex.org/W2049965683","https://openalex.org/W2128973682","https://openalex.org/W1940919858","https://openalex.org/W2031297073","https://openalex.org/W1998084629","https://openalex.org/W2035143815","https://openalex.org/W2132889831","https://openalex.org/W3187000984"],"abstract_inverted_index":{"Multidimensional":[0],"three-parameter":[1],"logistic":[2,71],"model":[3,72,113,144,148,153],"(M3PLM)":[4],"often":[5],"faces":[6],"poor":[7],"recovery":[8,151],"of":[9,16,57,82,110],"parameters":[10,83],"due":[11],"to":[12,21,41,53,60,105,132],"overestimation":[13],"or":[14],"underestimation":[15],"guess":[17],"parameters.":[18],"In":[19,118],"order":[20],"more":[22],"reasonably":[23],"consider":[24],"the":[25,42,54,80,87,93,108,111,115,135,142,146,158,171,174],"participant\u2019s":[26,94],"guesses,":[27],"this":[28],"study":[29,169],"proposed":[30],"a":[31,46,161],"new":[32,65],"multidimensional":[33,69],"IRT":[34,175],"modeling":[35],"based":[36],"on":[37],"2PLE,":[38],"which":[39,155],"equal":[40],"guessing":[43,62,75],"parameter":[44,150],"with":[45,73,114,134],"function":[47],"that":[48,141,157],"integrates":[49],"item":[50],"characteristic":[51],"according":[52],"ability":[55],"level":[56],"an":[58,128],"examinee":[59],"quantify":[61],"behavior.":[63],"Our":[64],"model,":[66,77,89],"named":[67],"as":[68,127],"two-parameter":[70],"ability-item-based":[74],"(M2PL-AIG)":[76],"not":[78],"only":[79],"number":[81],"is":[84,125,160],"smaller":[85],"than":[86],"M3PL":[88,98,116,136,147],"but":[90],"also":[91],"considers":[92],"guesses":[95],"just":[96],"like":[97],"model.":[99,117,137],"Two":[100],"simulation":[101],"studies":[102],"were":[103],"conducted":[104],"fully":[106],"comparing":[107],"performance":[109],"M2PL-AIG":[112,143,159],"addition,":[119],"real":[120],"data":[121],"from":[122],"TIMSS":[123],"2011":[124],"used":[126],"application":[129],"illustration":[130],"and":[131,152,170],"compare":[133],"The":[138],"results":[139],"show":[140],"outperforms":[145],"in":[149],"fit,":[154],"indicates":[156],"rather":[162],"interesting":[163],"proposal,":[164],"surely":[165],"worth":[166],"some":[167],"further":[168],"consideration":[172],"by":[173],"community.":[176]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
