{"id":"https://openalex.org/W2326527644","doi":"https://doi.org/10.1080/10705511.2015.1118692","title":"Bootstrapping Confidence Intervals for Fit Indexes in Structural Equation Modeling","display_name":"Bootstrapping Confidence Intervals for Fit Indexes in Structural Equation Modeling","publication_year":2016,"publication_date":"2016-03-23","ids":{"openalex":"https://openalex.org/W2326527644","doi":"https://doi.org/10.1080/10705511.2015.1118692","mag":"2326527644"},"language":"en","primary_location":{"id":"doi:10.1080/10705511.2015.1118692","doi":"https://doi.org/10.1080/10705511.2015.1118692","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10705511.2015.1118692","pdf_url":null,"source":{"id":"https://openalex.org/S78020522","display_name":"Structural Equation Modeling A Multidisciplinary Journal","issn_l":"1070-5511","issn":["1070-5511","1532-8007"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","dongbi-c","erih-plus","jufo-1","ki-jl-1","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Structural Equation Modeling: A Multidisciplinary Journal","raw_type":"journal-article"},"volume":null,"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/A5063683994","display_name":"Xijuan Zhang","orcid":"https://orcid.org/0000-0001-9227-8867","observed_orcids":["https://orcid.org/0000-0001-9227-8867"]},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Xijuan Zhang","raw_affiliation_strings":["University of British Columbia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of British Columbia","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055786394","display_name":"Victoria Savalei","orcid":"https://orcid.org/0000-0001-8530-3251","observed_orcids":["https://orcid.org/0000-0001-8530-3251"]},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Victoria Savalei","raw_affiliation_strings":["University of British Columbia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of British Columbia","institution_ids":["https://openalex.org/I141945490"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5055786394"],"corresponding_institution_ids":["https://openalex.org/I141945490"],"apc_list":null,"apc_paid":null,"fwci":4.382,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":{"value":0.94003165,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"23","issue":"3","first_page":"392","last_page":"408"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10467","display_name":"Psychometric Methodologies and Testing","score":0.9541000127792358,"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":0.9541000127792358,"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":0.02889999933540821,"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/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.005900000222027302,"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/bootstrap-confidence-intervals","display_name":"bootstrap confidence intervals","score":0.8140000104904175},{"id":"https://openalex.org/keywords/rmsea","display_name":"RMSEA","score":0.6880000233650208},{"id":"https://openalex.org/keywords/comparative-fit-index","display_name":"comparative fit index","score":0.972000002861023},{"id":"https://openalex.org/keywords/goodness-of-fit-index","display_name":"goodness of fit index","score":0.9890000224113464},{"id":"https://openalex.org/keywords/chi-square-statistic","display_name":"chi-square statistic","score":0.7289999723434448},{"id":"https://openalex.org/keywords/coverage-rate","display_name":"coverage rate","score":0.5299999713897705}],"concepts":[{"id":"https://openalex.org/C207609745","wikidata":"https://www.wikidata.org/wiki/Q4944086","display_name":"Bootstrapping (finance)","level":2,"score":0.8577731847763062},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.7589995861053467},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.7421349287033081},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.6548399925231934},{"id":"https://openalex.org/C71104824","wikidata":"https://www.wikidata.org/wiki/Q1476639","display_name":"Structural equation modeling","level":2,"score":0.6524133682250977},{"id":"https://openalex.org/C132480984","wikidata":"https://www.wikidata.org/wiki/Q2034239","display_name":"Goodness of fit","level":2,"score":0.6475072503089905},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.5800279974937439},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5225409865379333},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.5020935535430908},{"id":"https://openalex.org/C2777205145","wikidata":"https://www.wikidata.org/wiki/Q4944080","display_name":"Bootstrap model","level":4,"score":0.4638732671737671},{"id":"https://openalex.org/C169857963","wikidata":"https://www.wikidata.org/wiki/Q1461038","display_name":"Test statistic","level":3,"score":0.4228534698486328},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.3325358033180237},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.2763732373714447},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.06748652458190918},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C109214941","wikidata":"https://www.wikidata.org/wiki/Q18334","display_name":"Particle physics","level":1,"score":0.0},{"id":"https://openalex.org/C79118098","wikidata":"https://www.wikidata.org/wiki/Q43101","display_name":"Boson","level":2,"score":0.0},{"id":"https://openalex.org/C14591024","wikidata":"https://www.wikidata.org/wiki/Q7778426","display_name":"Particle decay","level":3,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/10705511.2015.1118692","doi":"https://doi.org/10.1080/10705511.2015.1118692","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10705511.2015.1118692","pdf_url":null,"source":{"id":"https://openalex.org/S78020522","display_name":"Structural Equation Modeling A Multidisciplinary Journal","issn_l":"1070-5511","issn":["1070-5511","1532-8007"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","dongbi-c","erih-plus","jufo-1","ki-jl-1","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Structural Equation Modeling: A Multidisciplinary Journal","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":59,"referenced_works":["https://openalex.org/W611152568","https://openalex.org/W1560371066","https://openalex.org/W1913957972","https://openalex.org/W1968524945","https://openalex.org/W1971223956","https://openalex.org/W1971410477","https://openalex.org/W1991374387","https://openalex.org/W1992193527","https://openalex.org/W1995945562","https://openalex.org/W2000025407","https://openalex.org/W2003993603","https://openalex.org/W2005967696","https://openalex.org/W2006319807","https://openalex.org/W2006779932","https://openalex.org/W2008844726","https://openalex.org/W2011755304","https://openalex.org/W2013763545","https://openalex.org/W2014543370","https://openalex.org/W2016097394","https://openalex.org/W2018201949","https://openalex.org/W2018927020","https://openalex.org/W2020111686","https://openalex.org/W2020761311","https://openalex.org/W2027860872","https://openalex.org/W2030170328","https://openalex.org/W2030630447","https://openalex.org/W2032828899","https://openalex.org/W2034418568","https://openalex.org/W2034602811","https://openalex.org/W2034820849","https://openalex.org/W2042539525","https://openalex.org/W2046665151","https://openalex.org/W2048630522","https://openalex.org/W2049139564","https://openalex.org/W2050918499","https://openalex.org/W2052934174","https://openalex.org/W2056434135","https://openalex.org/W2060314804","https://openalex.org/W2065592277","https://openalex.org/W2067708868","https://openalex.org/W2071666535","https://openalex.org/W2077618113","https://openalex.org/W2085816378","https://openalex.org/W2105892385","https://openalex.org/W2117897510","https://openalex.org/W2118769530","https://openalex.org/W2119082688","https://openalex.org/W2130969147","https://openalex.org/W2134479314","https://openalex.org/W2141002481","https://openalex.org/W2149608872","https://openalex.org/W2163297822","https://openalex.org/W2164085284","https://openalex.org/W2168993315","https://openalex.org/W2327327889","https://openalex.org/W2784954700","https://openalex.org/W2799307137","https://openalex.org/W3106889297","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2724904441","https://openalex.org/W2030630447","https://openalex.org/W1536138986","https://openalex.org/W2067892816","https://openalex.org/W7169492509","https://openalex.org/W2333131160","https://openalex.org/W2767347943","https://openalex.org/W4399068220","https://openalex.org/W2024934382","https://openalex.org/W4401323391"],"abstract_inverted_index":{"Bootstrapping":[0],"approximate":[1],"fit":[2,15,56,80,102,139],"indexes":[3,16,57,81,140],"in":[4,167,260],"structural":[5],"equation":[6],"modeling":[7],"(SEM)":[8],"is":[9,46,63,72,108,135],"of":[10,33,96,112,180,243],"great":[11],"importance":[12],"because":[13,58,105],"most":[14,261],"do":[17],"not":[18,47,73],"have":[19],"tractable":[20],"analytic":[21],"distributions.":[22],"Model-based":[23],"bootstrap,":[24],"which":[25],"has":[26,157],"been":[27],"proposed":[28,124],"to":[29,75,128,163,176],"obtain":[30],"the":[31,34,39,61,67,86,91,100,113,145,150,154,158,164,168,178,181,185,210,213,225,228,237,250],"distribution":[32],"model":[35,239],"chi-square":[36,87],"statistic":[37],"under":[38,212,227,252],"null":[40,62],"hypothesis":[41],"(Bollen":[42],"&":[43],"Stine,":[44],"1992),":[45],"theoretically":[48],"appropriate":[49],"for":[50,55,78,137,188,206,221,246],"obtaining":[51],"confidence":[52],"intervals":[53],"(CIs)":[54],"it":[59],"assumes":[60],"exactly":[64],"true.":[65],"On":[66],"other":[68],"hand,":[69],"naive":[70,186,229],"bootstrap":[71,125,183,187,215,230,254],"expected":[74],"work":[76],"well":[77],"those":[79],"that":[82,121,141,153,205],"are":[83,142],"based":[84,143],"on":[85,144],"statistic,":[88],"such":[89],"as":[90],"root":[92,198],"mean":[93,199],"square":[94,200],"error":[95],"approximation":[97],"(RMSEA)":[98],"and":[99,131,184,196,208,248],"comparative":[101],"index":[103,194],"(CFI),":[104],"sample":[106],"noncentrality":[107,160,166],"a":[109,122,173],"biased":[110],"estimate":[111],"population":[114,156,159],"noncentrality.":[115],"In":[116],"this":[117],"article":[118],"we":[119],"argue":[120],"recently":[123],"approach":[126],"due":[127],"Yuan,":[129],"Hayashi,":[130],"Yanagihara":[132],"(YHY;":[133],"2007)":[134],"ideal":[136],"bootstrapping":[138],"chi-square.":[146],"This":[147],"method":[148],"transforms":[149],"data":[151],"so":[152],"\u201cparent\u201d":[155],"parameter":[161],"equal":[162],"estimated":[165],"original":[169],"sample.":[170],"We":[171,203],"conducted":[172],"simulation":[174],"study":[175],"evaluate":[177],"performance":[179],"YHY":[182,214],"4":[189],"indexes:":[190],"RMSEA,":[191],"CFI,":[192,209],"goodness-of-fit":[193],"(GFI),":[195],"standardized":[197],"residual":[201],"(SRMR).":[202],"found":[204],"RMSEA":[207],"CIs":[211,226,251],"had":[216,231,240,256],"relatively":[217],"good":[218],"coverage":[219,234,258],"rates":[220,235,259],"all":[222],"conditions,":[223],"whereas":[224],"very":[232],"low":[233],"when":[236],"fitted":[238],"large":[241],"degrees":[242],"freedom.":[244],"However,":[245],"GFI":[247],"SRMR,":[249],"both":[253],"methods":[255],"poor":[257],"conditions.":[262]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3}],"updated_date":"2026-08-15T07:11:24.734988","created_date":"2016-06-24T00:00:00"}