Publication:
Some remarks on estimating a covariance structure model from a sample correlation matrix

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dc.affiliation.dptoUC3M. Departamento de Estadísticaes
dc.contributor.authorMaydeu Olivares, Alberto
dc.contributor.authorHernández Estrada, Adolfo
dc.contributor.editorUniversidad Carlos III de Madrid. Departamento de Estadísticaes
dc.date.accessioned2011-01-18T18:08:52Z
dc.date.available2011-01-18T18:08:52Z
dc.date.issued2000-09
dc.description.abstractA popular model in structural equation modeling involves a multivariate normal density with a structured covariance matrix that has been categorized according to a set of thresholds. In this setup one may estimate the covariance structure parameters from the sample tetrachoricl polychoric correlations but only if the covariance structure is scale invariant. Doing so when the covariance structure is not scale invariant results in estimating a more restricted covariance structure than the one intended. When the covariance structure is not scale invariant, then the model parameters must be estimated jointly from the sample thresholds and tetrachoricl polychoric correlations. In general, when fitting a covariance structure from a sample correlation matrix one should consider the population correlation structure under the null hypothesis. This is obtained by pre and post-multiplying the covariance structure by a diagonal matrix consisting of the inverse of the square root of the diagonal of the covariance structure under consideration. We provide computer algebra code for assessing whether a covariance structure is scale invariant and for assessing the identification of threshold and correlation structures.es
dc.format.mimetypeapplication/octet-stream
dc.format.mimetypeapplication/octet-stream
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/10016/10009
dc.language.isoenges
dc.relation.ispartofseriesUC3M Working papers. Statistics and Econometricses
dc.relation.ispartofseries00-62es
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.ecienciaEstadísticaes
dc.subject.otherLisreles
dc.subject.otherMpluses
dc.subject.otherMathematicaes
dc.subject.otherTau-equivalent modeles
dc.subject.otherNnormal ogive modeles
dc.titleSome remarks on estimating a covariance structure model from a sample correlation matrixes
dc.typeworking paper*
dspace.entity.typePublication
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