Smith, D.M., Ridout, Martin S. (2005) Algorithms for finding locally and Bayesian optimal designs for binary dose-response models with control mortality. Journal of Statistical Planning and Inference, 33 (2). pp. 463-478. ISSN 0378-3758. (doi:10.1016/j.jspi.2004.01.017) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:9008)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: http://dx.doi.org/10.1016/j.jspi.2004.01.017 |
Abstract
Algorithms for finding optimal designs for three-parameter binary dose–response models that incorporate control mortality are described. Locally and Bayesian optimal designs for models with a range of link functions are considered. Design criteria looked at include D-optimal, DA-optimal and V-optimal designs, together with Ds-optimal designs where the control mortality parameter is regarded as a nuisance parameter. The range of prior distributions for the Bayesian optimal designs includes uniform, trivariate normal and a combination of a bivariate normal prior for the parameters of the underlying dose–response with an independent uniform prior for the control mortality parameter.
Item Type: | Article |
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DOI/Identification number: | 10.1016/j.jspi.2004.01.017 |
Uncontrolled keywords: | Generalized linear models; General equivalence theorem; Abbott's formula |
Subjects: | Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science |
Depositing User: | Martin Ridout |
Date Deposited: | 29 Jun 2011 15:18 UTC |
Last Modified: | 16 Nov 2021 09:47 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/9008 (The current URI for this page, for reference purposes) |
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