Penalized locally optimal experimental designs for nonlinear models

Abstract

Classical optimal design theory may produce experimental designs that are biologically or characteristically inappropriate. Often, there is a particular study goal along with many practical experimental concerns that a researcher may wish to include in the optimal design process. This article provides a technique that allows a researcher to incorporate desired experimental characteristics into an adjusted optimal design criterion. This technique uses a weighted overall desirability function to penalize the optimal design criterion. A researcher may define an overall desirability function using any number of individual desirability functions to influence the properties of an optimal experimental design. The methodology is illustrated with two dose-response examples.