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dc.contributor.authorEthington, Corinna A.en
dc.date.accessioned2015-07-10T20:00:17Zen
dc.date.available2015-07-10T20:00:17Zen
dc.date.issued1985en
dc.identifier.urihttp://hdl.handle.net/10919/54504en
dc.description.abstractThis study was an examination of the effect of type of correlation matrix on the robustness of LISREL maximum likelihood and unweighted least squares structural parameter estimates for models with categorical manifest variables. Two types of correlation matrices were analyzed; one containing Pearson product-moment correlations and one containing tetrachoric, polyserial, and product-moment correlations as appropriate. Using continuous variables generated according to the equations defining the population model, three cases were considered by dichotomizing some of the variables with varying degrees of skewness. When Pearson product-moment correlations were used to estimate associations involving dichotomous variables, the structural parameter estimates were biased when skewness was present in the dichotomous variables. Moreover, the degree of bias was consistent for both the maximum likelihood and unweighted least squares estimates. The standard errors of the estimates were found to be inflated, making significance tests unreliable. The analysis of mixed matrices produced average estimates that more closely approximated the model parameters except in the case where the dichotomous variables were skewed in opposite directions. However, since goodness-of-fit statistics and standard errors are not available in LISREL when tetrachoric and polyserial correlations are used, the unbiased estimates are not of practical significance. Until alternative computer programs are available that employ distribution-free estimation procedures that consider the skewness and kurtosis of the variables, researchers are ill-advised to employ LISREL in the estimation of structural equation models containing skewed categorical manifest variables.en
dc.format.extentviii, 122 leavesen
dc.format.mimetypeapplication/pdfen
dc.language.isoen_USen
dc.publisherVirginia Polytechnic Institute and State Universityen
dc.relation.isformatofOCLC# 13284450en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectLISREL (Computer file)en
dc.subject.lccLD5655.V856 1985.E834en
dc.subject.lcshFactor analysis -- Data processingen
dc.subject.lcshMathematical statistics -- Data processingen
dc.subject.lcshMatricesen
dc.titleThe robustness of LISREL estimates in structural equation models with categorical dataen
dc.typeDissertationen
dc.contributor.departmentEducational Research and Evaluationen
dc.description.degreePh. D.en
thesis.degree.namePh. D.en
thesis.degree.leveldoctoralen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.disciplineEducational Research and Evaluationen
dc.type.dcmitypeTexten


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