{"id":"https://openalex.org/W1484050280","doi":"https://doi.org/10.1111/j.1745-3984.2010.00127.x","title":"A Strategy for Developing a Common Metric in Item Response Theory When Parameter Posterior Distributions Are Known","display_name":"A Strategy for Developing a Common Metric in Item Response Theory When Parameter Posterior Distributions Are Known","publication_year":2011,"publication_date":"2011-03-01","ids":{"openalex":"https://openalex.org/W1484050280","doi":"https://doi.org/10.1111/j.1745-3984.2010.00127.x","mag":"1484050280"},"language":"en","primary_location":{"id":"doi:10.1111/j.1745-3984.2010.00127.x","doi":"https://doi.org/10.1111/j.1745-3984.2010.00127.x","is_oa":false,"landing_page_url":"https://doi.org/10.1111/j.1745-3984.2010.00127.x","pdf_url":null,"source":{"id":"https://openalex.org/S30638350","display_name":"Journal of Educational Measurement","issn_l":"0022-0655","issn":["0022-0655","1745-3984"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","dongbi-c","erih-plus","ki-jl-2","norway-2","poland-70","russia-white-list-2","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":"Journal of Educational Measurement","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"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/A5102852506","display_name":"Peter Baldwin","orcid":"https://orcid.org/0000-0003-3472-0172","observed_orcids":["https://orcid.org/0000-0003-3472-0172"]},"institutions":[{"id":"https://openalex.org/I1293309919","display_name":"National Board of Medical Examiners","ror":"https://ror.org/04tsmra86","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1293309919"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Peter Baldwin","raw_affiliation_strings":["National Board of Medical Examiners"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Board of Medical Examiners","institution_ids":["https://openalex.org/I1293309919"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5102852506"],"corresponding_institution_ids":["https://openalex.org/I1293309919"],"apc_list":{"value":3040,"currency":"USD","value_usd":3040},"apc_paid":null,"fwci":1.2484,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.80825967,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":96},"biblio":{"volume":"48","issue":"1","first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10467","display_name":"Psychometric Methodologies and Testing","score":0.9976000189781189,"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":0.9976000189781189,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.0010000000474974513,"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/T12884","display_name":"Educational Assessment and Pedagogy","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/3304","display_name":"Education"},"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/common-metric","display_name":"common metric","score":0.8180000185966492},{"id":"https://openalex.org/keywords/item-response-theory","display_name":"item response theory","score":0.8270000219345093},{"id":"https://openalex.org/keywords/error-propagation","display_name":"error propagation","score":0.7229999899864197},{"id":"https://openalex.org/keywords/sampling-strategy","display_name":"sampling strategy","score":0.6010000109672546},{"id":"https://openalex.org/keywords/coverage-properties","display_name":"coverage properties","score":0.6610000133514404},{"id":"https://openalex.org/keywords/point-estimates","display_name":"point estimates","score":0.3619999885559082}],"concepts":[{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.7129070162773132},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5827431082725525},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.53269362449646},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.5301371812820435},{"id":"https://openalex.org/C41426520","wikidata":"https://www.wikidata.org/wiki/Q1192065","display_name":"Point estimation","level":2,"score":0.5224082469940186},{"id":"https://openalex.org/C19875794","wikidata":"https://www.wikidata.org/wiki/Q1207340","display_name":"Item response theory","level":3,"score":0.5145296454429626},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5126720666885376},{"id":"https://openalex.org/C51110983","wikidata":"https://www.wikidata.org/wiki/Q16503490","display_name":"Overconfidence effect","level":2,"score":0.5074209570884705},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.47399914264678955},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.46928226947784424},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4594164490699768},{"id":"https://openalex.org/C2983447341","wikidata":"https://www.wikidata.org/wiki/Q1413083","display_name":"Model parameter","level":2,"score":0.43921852111816406},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.41278278827667236},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3799980878829956},{"id":"https://openalex.org/C171606756","wikidata":"https://www.wikidata.org/wiki/Q506132","display_name":"Psychometrics","level":2,"score":0.18326669931411743},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.10537439584732056},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.09852108359336853},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1111/j.1745-3984.2010.00127.x","doi":"https://doi.org/10.1111/j.1745-3984.2010.00127.x","is_oa":false,"landing_page_url":"https://doi.org/10.1111/j.1745-3984.2010.00127.x","pdf_url":null,"source":{"id":"https://openalex.org/S30638350","display_name":"Journal of Educational Measurement","issn_l":"0022-0655","issn":["0022-0655","1745-3984"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","dongbi-c","erih-plus","ki-jl-2","norway-2","poland-70","russia-white-list-2","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":"Journal of Educational Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W96361263","https://openalex.org/W103719185","https://openalex.org/W1547573674","https://openalex.org/W1547716543","https://openalex.org/W1963784071","https://openalex.org/W1964052265","https://openalex.org/W1977914032","https://openalex.org/W1980878481","https://openalex.org/W1986021671","https://openalex.org/W2059625946","https://openalex.org/W2089588599","https://openalex.org/W2135972812","https://openalex.org/W2140869847","https://openalex.org/W2153433904","https://openalex.org/W2158518800","https://openalex.org/W2482834658","https://openalex.org/W2505213109","https://openalex.org/W2524380279"],"related_works":["https://openalex.org/W6959198792","https://openalex.org/W4251714720","https://openalex.org/W2097563491","https://openalex.org/W2341346793","https://openalex.org/W1912885464","https://openalex.org/W2044306689","https://openalex.org/W1592396744","https://openalex.org/W2795035211","https://openalex.org/W2317183087","https://openalex.org/W7051994981"],"abstract_inverted_index":{"Growing":[0],"interest":[1],"in":[2,105,142],"fully":[3],"Bayesian":[4],"item":[5],"response":[6],"models":[7],"begs":[8],"the":[9,42,106,137],"question:":[10],"To":[11],"what":[12],"extent":[13],"can":[14,61],"model":[15,29,111],"parameter":[16,30,55,112],"posterior":[17,39,113],"draws":[18,40,114],"enhance":[19],"existing":[20],"practices?":[21],"One":[22],"practice":[23],"that":[24,73,136],"has":[25],"traditionally":[26],"relied":[27],"on":[28],"point":[31],"estimates":[32,56,68],"but":[33],"may":[34,118],"be":[35,62,70,119],"improved":[36],"by":[37],"using":[38,133,152],"is":[41,83,86,94,98,131],"development":[43],"of":[44,89],"a":[45,77,87,123],"common":[46,78],"metric":[47],"for":[48,121],"two":[49],"independently":[50,58],"calibrated":[51,59],"test":[52],"forms.":[53],"Before":[54],"from":[57],"forms":[60,75],"compared,":[63],"at":[64],"least":[65],"one":[66],"form's":[67],"must":[69],"adjusted":[71,107,143],"such":[72],"both":[74],"share":[76],"metric.":[79],"Because":[80],"this":[81,128],"adjustment":[82],"estimated,":[84],"there":[85],"propagation":[88],"error":[90],"effect":[91,97],"when":[92,110],"it":[93,117,130],"applied.":[95],"This":[96],"typically":[99],"ignored,":[100],"which":[101],"leads":[102],"to":[103],"overconfidence":[104],"estimates;":[108],"yet,":[109],"are":[115],"available,":[116],"accounted":[120],"with":[122,145],"simple":[124],"sampling":[125,139],"strategy.":[126],"In":[127],"paper,":[129],"shown":[132],"simulated":[134],"data":[135],"proposed":[138],"strategy":[140],"results":[141],"posteriors":[144],"superior":[146],"coverage":[147],"properties":[148],"than":[149],"those":[150],"obtained":[151],"traditional":[153],"point-estimate-based":[154],"methods.":[155]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2016-06-24T00:00:00"}