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dc.contributor.authorDette, Holgerde
dc.contributor.authorHolland-Letz, Timde
dc.contributor.authorPepelyshev, Andreyde
dc.date.accessioned2009-10-29T10:10:24Z-
dc.date.available2009-10-29T10:10:24Z-
dc.date.issued2009-07-28de
dc.identifier.urihttp://hdl.handle.net/2003/26482-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-12660-
dc.description.abstractWe consider the problem of optimal design of experiments for random effects models, especially population models, where a small number of correlated observations can be taken on each individual, while the observations corresponding to different individuals can be assumed to be uncorrelated. We focus on c-optimal design problems and show that the classical equivalence theorem and the famous geometric characterization of Elfving (1952) from the case of uncorrelated data can be adapted to the problem of selecting optimal sets of observations for the n individual patients. The theory is demonstrated in a linear model with correlated observations and a nonlinear random effects population model, which is commonly used in pharmacokinetics.en
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB 823; 7/2009de
dc.subjectc-optimal designen
dc.subjectcorrelated observationsen
dc.subjectElfving's theoremen
dc.subjectgeometric characterizationen
dc.subjectlocally optimal designen
dc.subjectmixed modelsen
dc.subjectpharmacokinetic modelsen
dc.subjectrandom effectsen
dc.subject.ddc310de
dc.subject.ddc330de
dc.subject.ddc620de
dc.titleA geometric characterization of c-optimal designs for regression models with correlated observationsen
dc.typeTextde
dc.type.publicationtypereportde
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 823

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