Authors: Dette, Holger
Holland-Letz, Tim
Pepelyshev, Andrey
Title: A geometric characterization of c-optimal designs for regression models with correlated observations
Language (ISO): en
Abstract: We 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.
Subject Headings: c-optimal design
correlated observations
Elfving's theorem
geometric characterization
locally optimal design
mixed models
pharmacokinetic models
random effects
Issue Date: 2009-07-28
Appears in Collections:Sonderforschungsbereich (SFB) 823

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