Bayesian L-optimal exact design of experiments for biological kinetic models

Gilmour, Steven G. and Trinca, Luzia A. (2011) Bayesian L-optimal exact design of experiments for biological kinetic models. Journal of the Royal Statistical Society Series C (Applied Statistics), 61, (2), 237-251. (doi:10.1111/j.1467-9876.2011.01003.x).


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Data from experiments in steady-state enzyme kinetic studies and radiological binding assays are usually analyzed by fitting nonlinear models developed from biochemical theory. Designing experiments for fitting nonlinear models is complicated by the fact that the variances of parameter estimates depend on the unknown values of these parameters and Bayesian optimal exact design for nonlinear least squares analysis is often recommended. It has been difficult to implement Bayesian L optimal exact design, but we show how it can be done using a computer algebra package to invert the information matrix, sampling from the prior distribution to evaluate the optimality criterion for candidate designs and implementing an exchange algorithm to search for candidate designs. These methods are applied to finding op- timal designs for the motivating applications in biological kinetics, in the context of which some practical problems are discussed. A sensitivity study shows that the use of a prior distribution can be essential, as is careful specification of that prior.

Item Type: Article
Digital Object Identifier (DOI): doi:10.1111/j.1467-9876.2011.01003.x
ISSNs: 0035-9254 (print)
1467-9876 (electronic)
Subjects: H Social Sciences > HA Statistics
Q Science > QA Mathematics
Divisions : University Structure - Pre August 2011 > School of Mathematics > Statistics
ePrint ID: 180619
Accepted Date and Publication Date:
Date Deposited: 14 Apr 2011 15:42
Last Modified: 31 Mar 2016 13:35

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