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, Memphis, USA, 13 - 15 May 2005.

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Description/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.

Item Type: Conference or Workshop Item (Speech)
Subjects: Q Science > QA Mathematics
H Social Sciences > HA Statistics
Divisions: University Structure - Pre August 2011 > School of Mathematics
University Structure - Pre August 2011 > Southampton Statistical Sciences Research Institute
University Structure - Pre August 2011 > School of Mathematics > Statistics
ePrint ID: 15868
Date Deposited: 06 Jun 2005
Last Modified: 27 Mar 2014 18:06
URI: http://eprints.soton.ac.uk/id/eprint/15868

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