Optimal designs for discriminating dose response models in toxicology studies

Dette, Holger; Pepelyshev, Andrey; Shpilev, Piter; Wong, Weng K.

Optimal designs for discriminating dose response models in toxicology studies

dc.contributor.author	Dette, Holger	de
dc.contributor.author	Pepelyshev, Andrey	de
dc.contributor.author	Shpilev, Piter	de
dc.contributor.author	Wong, Weng K.	de
dc.date.accessioned	2009-10-29T10:13:23Z
dc.date.available	2009-10-29T10:13:23Z
dc.date.issued	2009-07-06	de
dc.description.abstract	We consider design issues for toxicology studies when we have a continuous response but the true mean response is only known to be a member in a class of nested models. This class of models were proposed by toxicologists who were concerned with only estimation problems. We develop robust and effcient designs for model discrimination and optimal designs for estimating parameters in the selected model at the same time. In particular, we propose designs that maximize the minimum of D- or D_1-efficiencies over all models in the given class. We show that these optimal designs are efficient for determining an appropriate model from the postulated class, quite efficient for estimating model parameters in the identified model and also robust with respect to model mis-specification. To facilitate use of these designs in practice, we have also constructed a web site to enable practitioners to generate optimal designs for their problems.	en
dc.identifier.uri	http://hdl.handle.net/2003/26485
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-12667
dc.language.iso	en	de
dc.relation.ispartofseries	Discussion Paper / SFB 823; 11/2009	de
dc.subject	continuous design	en
dc.subject	local optimal design	en
dc.subject	maximin optimal design	en
dc.subject	model discrimination	en
dc.subject	robust design	en
dc.subject.ddc	310	de
dc.subject.ddc	330	de
dc.subject.ddc	620	de
dc.title	Optimal designs for discriminating dose response models in toxicology studies	en
dc.type	Text	de
dc.type.publicationtype	report	de
dcterms.accessRights	open access

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