Smith, D.M. and Ridout, Martin S. Algorithms for finding locally and Bayesian optimal designs for binary dose-response models with control mortality. Journal of Statistical Planning and Inference, 33 . pp. 463-478. ISSN 0378-3758. (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)
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.
|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:||09 May 2014 13:10|
|Resource URI:||https://kar.kent.ac.uk/id/eprint/9008 (The current URI for this page, for reference purposes)|