{"id":"https://openalex.org/W1976322966","doi":"https://doi.org/10.1080/03610910802645362","title":"Model Selection for Linear Mixed Models Using Predictive Criteria","display_name":"Model Selection for Linear Mixed Models Using Predictive Criteria","publication_year":2009,"publication_date":"2009-02-06","ids":{"openalex":"https://openalex.org/W1976322966","doi":"https://doi.org/10.1080/03610910802645362","mag":"1976322966"},"language":"en","primary_location":{"id":"doi:10.1080/03610910802645362","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610910802645362","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/A5100384655","display_name":"Jun Wang","orcid":"https://orcid.org/0000-0001-9223-2615"},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun Wang","raw_affiliation_strings":["Department of Statistics Brigham Young University Provo Utah USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics Brigham Young University Provo Utah USA","institution_ids":["https://openalex.org/I100005738"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033625610","display_name":"G. Bruce Schaalje","orcid":null},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"G. Bruce Schaalje","raw_affiliation_strings":["Department of Statistics Brigham Young University Provo Utah USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics Brigham Young University Provo Utah USA","institution_ids":["https://openalex.org/I100005738"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.987,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.86727104,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"38","issue":"4","first_page":"788","last_page":"801"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9994999766349792,"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":0.9994999766349792,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9994000196456909,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9984999895095825,"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/mixed-model","display_name":"Mixed model","score":0.5492352247238159},{"id":"https://openalex.org/keywords/generalized-linear-mixed-model","display_name":"Generalized linear mixed model","score":0.5453729629516602},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4685298800468445},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.4258134365081787},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37376803159713745},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.36315250396728516},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3622497618198395},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.19353407621383667}],"concepts":[{"id":"https://openalex.org/C16012445","wikidata":"https://www.wikidata.org/wiki/Q1501135","display_name":"Mixed model","level":2,"score":0.5492352247238159},{"id":"https://openalex.org/C153720581","wikidata":"https://www.wikidata.org/wiki/Q5532490","display_name":"Generalized linear mixed model","level":2,"score":0.5453729629516602},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4685298800468445},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.4258134365081787},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37376803159713745},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.36315250396728516},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3622497618198395},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19353407621383667}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610910802645362","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610910802645362","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1965804254","https://openalex.org/W1968371014","https://openalex.org/W1981747359","https://openalex.org/W1981903823","https://openalex.org/W1985697998","https://openalex.org/W2006779293","https://openalex.org/W2019173334","https://openalex.org/W2032901375","https://openalex.org/W2037481133","https://openalex.org/W2044520105","https://openalex.org/W2050297026","https://openalex.org/W2058815839","https://openalex.org/W2060755763","https://openalex.org/W2071527134","https://openalex.org/W2086561872","https://openalex.org/W2113037126","https://openalex.org/W2124269493","https://openalex.org/W2168175751","https://openalex.org/W2313339984","https://openalex.org/W2324191961","https://openalex.org/W4238463311","https://openalex.org/W4251263574"],"related_works":["https://openalex.org/W4293051593","https://openalex.org/W2356286374","https://openalex.org/W2477652392","https://openalex.org/W2033200554","https://openalex.org/W2005816970","https://openalex.org/W1992914993","https://openalex.org/W2152981472","https://openalex.org/W145207717","https://openalex.org/W2922528260","https://openalex.org/W1999504378"],"abstract_inverted_index":{"Predictive":[0],"criteria,":[1],"including":[2],"the":[3,9,15,27,47,50,59,69,107,112,118,128],"adjusted":[4,10,45],"squared":[5],"multiple":[6],"correlation":[7,12],"coefficient,":[8,13],"concordance":[11],"and":[14,42,106,111],"predictive":[16,95],"error":[17],"sum":[18],"of":[19,37,39,49,93,102,121,123],"squares,":[20],"are":[21],"available":[22],"for":[23,46,78,90],"model":[24,79],"selection":[25,80,87,122],"in":[26],"linear":[28],"mixed":[29],"model.":[30,51],"These":[31,72],"criteria":[32,73,96],"all":[33],"involve":[34],"some":[35],"sort":[36],"comparison":[38],"observed":[40],"values":[41,54],"predicted":[43,53],"values,":[44],"complexity":[48],"The":[52,115],"can":[55],"be":[56],"conditional":[57],"on":[58,66],"random":[60,70],"effects":[61],"or":[62],"marginal,":[63],"i.e.,":[64],"based":[65],"averages":[67],"over":[68],"effects.":[71],"have":[74],"not":[75],"been":[76],"investigated":[77],"success.":[81],"We":[82],"used":[83],"simulations":[84,116],"to":[85],"investigate":[86],"success":[88,143],"rates":[89],"several":[91,100],"versions":[92,101],"these":[94],"as":[97,99],"well":[98],"Akaike's":[103],"information":[104,109],"criterion":[105],"Bayesian":[108],"criterion,":[110],"pseudo":[113],"F-test.":[114],"involved":[117],"simple":[119],"scenario":[120],"a":[124],"fixed":[125],"parameter":[126],"when":[127],"covariance":[129],"structure":[130],"is":[131],"known.":[132],"Several":[133],"variance\u2013covariance":[134],"structures":[135],"were":[136],"used.":[137],"For":[138],"compound":[139],"symmetry":[140],"structures,":[141],"higher":[142],"r...":[144]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
