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 |
| Item ID: | 15868 |
| Date Deposited: | 06 Jun 2005 |
| Last Modified: | 02 Mar 2012 11:24 |
| Contributors: | Woods, D. C. (Author) |
| Date: | 15 May 2005 |
| Status: | Unpublished |
| URI: | http://eprints.soton.ac.uk/id/eprint/15868 |
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