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dc.contributor.authorBijleveld, Catrien C. J. H.
dc.contributor.authorVan der Burg, Eeke
dc.date.accessioned2008-03-12T15:54:16Z
dc.date.available2008-03-12T15:54:16Z
dc.date.issued1993
dc.identifier.citationBijleveld, Catrien C. J. H.; Van der Burg, Eeke. " Longitudinal K-sets analysis using lagged variables". Qüestiió. 1993, vol.17, núm.3
dc.identifier.issn0210-8054 (versió paper)
dc.identifier.urihttp://hdl.handle.net/2099/4611
dc.description.abstractWe present an application of nonlinear Generalised Canonical Analysis (GCA) for analysing longitudinal data. The application uses lagged versions of variables to accomodate the time-dependence in the measurements. The usefulness of the proposed method is illustrated in an example from developmental psychology, in which we explore the relationship between mother and child dyadic interaction during the first six months after birth, demonstrating how child behaviour can elicit mother behaviour. We discuss the relationship between our proposed method and the most closely resembling SERIALS (Van Buuren, 1990) method for nonlinear time series analysis.
dc.format.extent12 p.
dc.language.isoeng
dc.publisherInstitut d'estadística de Catalunya
dc.rightsAttribution-NonCommercial-NoDerivs 2.5 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/es/
dc.subject.lcshMultivariate analysis
dc.subject.otherGeneralised canonical analysis
dc.subject.otherOptimal scaling
dc.subject.otherLagged variables
dc.subject.otherDevelopmental research
dc.titleLongitudinal K-sets analysis using lagged variables
dc.title.alternativeAnálisis de K-conjuntos longitudinales mediante variables retardadas
dc.typeArticle
dc.subject.lemacAnàlisi multivariable
dc.subject.amsClassificació AMS::62 Statistics::62H Multivariate analysis
dc.rights.accessOpen Access


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