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dc.contributor.authorNæs, Tormod
dc.contributor.authorRomano, Rosaria
dc.contributor.authorTomic, Oliver
dc.contributor.authorMåge, Ingrid
dc.contributor.authorSmilde, Age K.
dc.contributor.authorLiland, Kristian Hovde
dc.identifier.citationJournal of Chemometrics. 2020, .en_US
dc.description.abstractThis paper is about the use of the multiblock regression method sequential and orthogonalized partial least squares (SO-PLS) for path modeling. The paper is a follow up of previously published papers on the same topic and presents a number of new results for the method. First of all, the paper discusses more thoroughly the aspect of how to incorporate blocks in the models and relates this to standard concepts in the area of graphical modeling. Second, the paper defines the concept of direct and indirect effects more precisely in terms of population parameters and shows how they are related to the additional effect in SO-PLS modeling. The paper illustrates the theory by simple graphs, simulations, and a real example from process monitoring.en_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.subjectGraphical modellingen_US
dc.subjectGraphical modellingen_US
dc.subjectCommon componentsen_US
dc.subjectCommon componentsen_US
dc.subjectPath analysisen_US
dc.subjectPath analysisen_US
dc.titleSequential and orthogonalized PLS (SO-PLS) regression for path analysis: Order of blocks and relations between effectsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.source.journalJournal of Chemometricsen_US
dc.relation.projectNofima AS: 201702en_US
dc.relation.projectNorges forskningsråd: 262308en_US
dc.relation.projectNofima AS: 11897en_US
dc.relation.projectNorges forskningsråd: 269264en_US
dc.relation.projectNofima AS: 11878en_US
dc.relation.projectNofima AS: 11958en_US

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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal