Title
Optimal Design for Mixed Effects Models
Speaker
Timothy H. Waterhouse, Eli Lilly and Company
Abstract
Mixed effects models, which allow the model parameters to vary randomly between blocks, are commonly used in pharmacometrics when modeling pharmacokinetic and pharmacodynamic data. In these cases, each patient is treated as a ‘block’ so that parameters such as the rate at which the body clears a drug may vary from patient to patient.
This talk outlines some approaches to designing experiments for such models when the aim is to minimise the confidence region of parameter estimates. Such approaches are based on the information matrix, the calculation of which becomes rather perilous for nonlinear and generalised linear models when random effects are introduced.
This is joint work with John Eccleston and Stephen Duffull at the University of Queensland, Australia.
Meet the speaker in Room 212 Cockins Hall at 4:30 p.m. Refreshments will be served.
