Smith, D.M. and Ridout, M.S. Algorithms for finding locally and Bayesian optimal designs for binary dose-response models with control mortality. Journal of Statistical Planning & Inference, 33 . pp. 463-478.
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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 |
|---|---|
| Subjects: | Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics |
| Divisions: | Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science |
| Depositing User: | Martin S Ridout |
| Date Deposited: | 29 Jun 2011 15:18 |
| Last Modified: | 13 Dec 2011 13:18 |
| Resource URI: | http://kar.kent.ac.uk/id/eprint/9008 (The current URI for this page, for reference purposes) |
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