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Fusion of data sets in multivariate linear regression with errors-in-variables

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dc.contributor.author Satorra, Albert
dc.contributor.other Universitat Pompeu Fabra. Departament d'Economia i Empresa
dc.date.accessioned 2017-07-26T12:07:57Z
dc.date.available 2017-07-26T12:07:57Z
dc.date.issued 1996-10-01
dc.identifier https://econ-papers.upf.edu/ca/paper.php?id=183
dc.identifier.citation Classification and Knowledge Organization, (1997), pp. 195-207
dc.identifier.uri http://hdl.handle.net/10230/1235
dc.description.abstract We consider the application of normal theory methods to the estimation and testing of a general type of multivariate regression models with errors--in--variables, in the case where various data sets are merged into a single analysis and the observable variables deviate possibly from normality. The various samples to be merged can differ on the set of observable variables available. We show that there is a convenient way to parameterize the model so that, despite the possible non--normality of the data, normal--theory methods yield correct inferences for the parameters of interest and for the goodness--of--fit test. The theory described encompasses both the functional and structural model cases, and can be implemented using standard software for structural equations models, such as LISREL, EQS, LISCOMP, among others. An illustration with Monte Carlo data is presented.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries Economics and Business Working Papers Series; 183
dc.rights L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.title Fusion of data sets in multivariate linear regression with errors-in-variables
dc.type info:eu-repo/semantics/workingPaper
dc.date.modified 2017-07-23T02:02:42Z
dc.subject.keyword asymptotic robustness
dc.subject.keyword multivariate regression
dc.subject.keyword asymptotic efficiency
dc.subject.keyword normal theory methods
dc.subject.keyword multi--samples
dc.subject.keyword errors--in--variables
dc.subject.keyword Statistics, Econometrics and Quantitative Methods
dc.rights.accessRights info:eu-repo/semantics/openAccess

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