Vis enkel innførsel

dc.contributor.authorGrønneberg, Steffen
dc.contributor.authorFoldnes, Njål
dc.date.accessioned2019-03-20T13:42:37Z
dc.date.available2019-03-20T13:42:37Z
dc.date.created2018-11-08T13:06:10Z
dc.date.issued2018
dc.identifier.issn1070-5511
dc.identifier.urihttp://hdl.handle.net/11250/2590880
dc.description.abstractOver the last few decades, many robust statistics have been proposed in order to assess the fit of structural equation models. To date, however, no clear recommendations have emerged as to which test statistic performs best. It is likely that no single statistic will universally outperform all contenders across all conditions of data, sample size, and model characteristics. In a real-world situation, a researcher must choose which statistic to report. We propose a bootstrap selection mechanism that identifies the test statistic that exhibits the best performance under the given data and model conditions among any set of candidates. This mechanism eliminates the ambiguity of the current practice and offers a wide array of test statistics available for reporting. In a Monte Carlo study, the bootstrap selector demonstrated promising performance in controlling Type I errors compared to current test statistics.nb_NO
dc.language.isoengnb_NO
dc.publisherTaylor and Francisnb_NO
dc.subjectBootstrappingnb_NO
dc.subjectStructural equation modelingnb_NO
dc.titleTesting Model Fit by Bootstrap Selectionnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.journalStructural Equation Modelingnb_NO
dc.identifier.doi10.1080/10705511.2018.1503543
dc.identifier.cristin1628359
cristin.unitcode158,3,0,0
cristin.unitnameInstitutt for samfunnsøkonomi
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode2


Tilhørende fil(er)

Thumbnail

Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel