Efficient experimental designs for sigmoidal growth models

Abstract

For the Weibull-and Richards-regression model robust designs are determined by maximizing a minimum of D-or D 1 -efficiencies, taken over a certain range of the non-linear parameters. It is demonstrated that the derived designs yield a satisfactory solution of the optimal design problem for this type of model in the sense that these designs are efficient and robust with respect to misspecification of the unknown parameters. Moreover, the designs can also be used for testing the postulated form of the regression model against a simplified sub-model.

Evaluation of the Fisher information matrix in nonlinear mixed effect models using adaptive Gaussian quadrature

“…Alternatives, such as adaptive designs (Leonov and Miller, 2009;Foo and Duffull, 2012) or robust designs based on Bayesian criteria (Han and Chaloner, 2004;Dette and Pepelyshev, 2008;Gotwalt et al, 2009;Abebe et al, 2014) would be interesting to explore.…”

Rancangan D-Optimal Model Michaelis Menten Dan Emax Dengan Matlab

“…Rancangan D-optimal untuk model nonlinear telah banyak dilakukan diantaranya Dette and Pepelyshev [2] . Li [5] menggunakan model regresi…”

Bioassay case study applying the maximin D‐optimal design algorithm to the four‐parameter logistic model

“…The maximin D‐optimal design selects a set of concentration points that is optimal for the worst‐case curve shape. Dette and Pepelyshev extended the general theory to show that the approach is applicable to sigmoidal nonlinear growth models, in particular, the exponential regression and Weibull models. Using the theoretical basis they developed, in this paper, we apply their approach to another sigmoidal model, the 4PL, and construct a maximin D‐optimal design.…”