Show simple item record

dc.contributor.authorSmith, C.
dc.contributor.authorCribbie, Robert
dc.date.accessioned2018-06-01T16:21:51Z
dc.date.available2018-06-01T16:21:51Z
dc.date.issued2013
dc.identifier.citationSmith, C. & Cribbie, R. A. (2013). Significance testing in structural equation modeling: Incorporating parameter dependencies into multiplicity controlling procedures. Structural Equation Modeling: An Interdisciplinary Journal, 20, 79-85. doi: 10.1080/10705511.2013.742385
dc.identifier.issn1070-5511
dc.identifier.uriDOI: 10.1080/10705511.2013.742385en_US
dc.identifier.urihttp://hdl.handle.net/10315/34590
dc.description.abstractWhen structural equation modeling (SEM) analyses are conducted, significance tests for all important model relationships (parameters including factor loadings, covariances, etc.) are typically conducted at a specified nominal Type I error rate (’). Despite the fact that many significance tests are often conducted in SEM, rarely is multiplicity control applied. Cribbie (2000, 2007) demonstrated that without some form of adjustment, the familywise Type I error rate can become severely inflated. Cribbie also confirmed that the popular Bonferroni method was overly conservative due to the correlations among the parameters in the model. The purpose of this study was to compare the Type I error rates and per-parameter power of traditional multiplicity strategies with those of adjusted Bonferroni procedures that incorporate not only the number of tests in a family, but also the degree of correlation between parameters. The adjusted Bonferroni procedures were found to produce per-parameter power rates higher than the original Bonferroni procedure without inflating the familywise error rate.en_US
dc.description.sponsorshipSocial Science and Humanities Research Council (SSHRC)
dc.language.isoenen_US
dc.publisherTaylor & Francis Groupen_US
dc.subjectmultiplicity controlen_US
dc.subjectBonferronien_US
dc.subjectfamilywise error controlen_US
dc.titleSignificance testing in structural equation modeling: Incorporating parameter dependencies into multiplicity controlling procedures.
dc.typeArticleen_US
dc.rights.journalhttps://www.tandfonline.com/loi/hsem20en_US
dc.rights.publisherhttps://www.tandfonline.com/en_US
dc.rights.articlehttps://www.tandfonline.com/doi/abs/10.1080/10705511.2013.742385


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record


All items in the YorkSpace institutional repository are protected by copyright, with all rights reserved except where explicitly noted.