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Designs for generalized linear models under model uncertainty

Woods, D. C. (2005) Designs for generalized linear models under model uncertainty At International Conference on Design of Experiments. 13 - 15 May 2005.

Record type: Conference or Workshop Item (Other)

Abstract

Standard factorial designs may sometimes be inadequate for experiments that aim to estimate a generalized linear model, for example, for describing a binary response in terms of several variables. A method is proposed for finding designs for such experiments which uses a criterion that allows for uncertainty in the link function, the linear predictor or the model parameters, together with a design search. Designs are assessed and compared by simulation of the distribution of efficiencies relative to locally optimal designs over a space of possible models. Designs are investigated for practical applications and their advantages are discussed.

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Published date: 15 May 2005
Venue - Dates: International Conference on Design of Experiments, 2005-05-13 - 2005-05-15
Organisations: Statistics

Identifiers

Local EPrints ID: 15868
URI: http://eprints.soton.ac.uk/id/eprint/15868
PURE UUID: 75d3d630-1d9e-4726-93b4-82ce8cf90b98

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Date deposited: 06 Jun 2005
Last modified: 17 Jul 2017 16:45

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